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Retrieved Entries: 461 [» Advanced search reports]
  1. Devendra K. Jangid, Neal R. Brodnik, Amil Khan, Michael G. Goebel, McLean P. Echlin, Tresa M. Pollock, Samantha H. Daly & B. S. Manjunath ,
    “3D Grain Shape Generation in Polycrystals Using Generative Adversarial Networks”,
    Integrating Materials and Manufacturing Innovation, Jan. 2022.
    [abstract] [PDF] [BibTex]
    Abstract preview: This paper presents a generative adversarial network (GAN) capable of producing realistic microstructure morphology features and demonstrates its capabilities on a dataset of crystalline titanium grai ... more
  2. Devendra K. Jangid, Neal R. Brodnik, Amil Khan, McLean P. Echlin, Tresa M. Pollock, Sam Daly, B.S. Manjunath,
    “3DMaterialGAN: Learning 3D Shape Representation from Latent Space for Materials Science Applications”,
    arXiv, Jul. 2020.
    [abstract] [PDF] [BibTex]
    Abstract preview: In the field of computer vision, unsupervised learning for 2D object generation has advanced rapidly in the past few years. However, 3D object generation has not garnered the same attention or success ... more
  3. Satish Kumar, Carlos Torres, Oytun Ulutan, Alana Ayasse, Dar Roberts, B. S. Manjunath,
    “Deep Remote Sensing Methods for Methane Detection in Overhead Hyperspectral Imagery”,
    The IEEE Winter Conference on Applications of Computer Vision (WACV) 2020, Mar. 2020.
    [abstract] [PDF] [BibTex]
    Abstract preview: Effective analysis of hyperspectral imagery is essential for gathering fast and actionable information of large areas affected by atmospheric and green house gases. Existing methods, which process hyp ... more
  4. Jiejun Xu, Vignesh Jagadeesh 2nd B.S. Manjunath,
    “Multi-label Learning with Fused Multimodal Bi-relational Graph”,
    IEEE Transaction on Multimedia, vol. 16, no. 2, pp. 403-412, Feb. 2014.
    [abstract] [PDF] [BibTex]
    Abstract preview: The problem of multi-label image classification using multiple feature modalities is considered in this work. Given a collection of images with partial labels, we first model the association between d ... more
  5. A. Baddeley, A. Jammalamadaka and G. Nair ,
    “Multitype point process analysis of spines on the dendrite network of a neuron”,
    Journal of Royal Statistical Society, vol. Series C (Applied Statistics), Feb. 2014.
    [abstract] [PDF] [BibTex]
    Abstract preview: We develop methods for analysing the spatial pattern of events, classified into several types, that occur on a network of lines. The motivation is the study of small protrusions called ‘spines’ whic ... more
  6. S. Karthikeyan, Vignesh Jagadeesh, Renuka Shenoy, Miguel Eckstein and B.S. Manjunath,
    “From Where and How to What We See”,
    IEEE International Conference on Computer Vision, Sydney, Dec. 2013.
    [abstract] [PDF] [BibTex]
    Abstract preview: Eye movement studies have confirmed that overt attention is highly biased towards faces and text regions in images. In this paper we explore a novel problem of predicting face and text regions in imag ... more
  7. Lakshmnanan Nataraj, Dhilung Kirat, B.S. Manjunath and Giovanni Vigna,
    “SARVAM: Search And RetrieVAl of Malware”,
    Annual Computer Security Applications Conference (ACSAC) Workshop on Next Generation Malware Attacks and Defense (NGMAD), New Orleans, Dec. 2013.
    [abstract] [PDF] [BibTex]
    Abstract preview: We present SARVAM, a system for content-based Search And RetrieVAl of Malware. In contrast with traditional static or dynamic analysis, SARVAM uses malware binary content to find similar malware. Give ... more
  8. S. Santhoshkumar, S. Karthikeyan and B. S. Manjunath,
    “Robust Multiple Object Tracking by Detection with Interacting Markov Chain Monte Carlo”,
    IEEE International Conference on Image Processing, Sep. 2013.
    [abstract] [PDF] [BibTex]
    Abstract preview: This paper presents a novel and computationally efficient multiobject tracking-by-detection algorithm with interacting particle filters. The proposed online tracking methodology could be scaled to hun ... more
  9. S. Karthikeyan, Diana Delibaltov, Utkarsh Gaur, Mei Jiang, David Williams and B.S. Manjunath,
    “Unified Probabilistic Framework for Simultaneous Detection and Tracking of Multiple Objects with Application To Bio-Image Sequences”,
    International Conference on Image Processing, Oct. 2012.
    [abstract] [PDF] [BibTex]
    Abstract preview: We present a detection based tracking algorithm for tracking melanosomes (organelles containing melanin) in time lapse image sequences imaged using bright field microscopy. Due to heavy imaging noise ... more
  10. Mahmudul Hasan, Yingying Zhu, Santhoshkumar Sunderrajan, Niloufar Pourian, B.S. Manjunath and Amit Roy Chowdhury,
    “Activity Analysis in Unconstrained Surveillance Videos”,
    Trecvid Technical Report, 2012.
    [abstract] [BibTex]
    Abstract preview: We detect seven activities defined by TRECVID SED task such as CellToEar, Embrace, ObjectPut, PeopleMeet, PeopleSplitUp, PersonRuns, and Pointing. We employ two different strategies to detec ... more
  11. Santhoshkumar Sunderrajan, Niloufar Pourian, Mahmudul Hasan, Yingying Zhu, B.S. Manjunath and Amit Roy Chowdhury ,
    “Discriminative Reranking based Video Object Retrieval”,
    Trecvid Technical Report, 2012.
    [abstract] [BibTex]
    Abstract preview: For the instance search task, we are given a set of query images with the corresponding textual meta-data and objects masks to retrieve video shots containing query objects from FLICKR video database. ... more
  12. V Jagadeesh, S Karthikeyan, B.S.Manjunath,
    “Spatio-Temporal Optical Flow Statistics (STOFS) for Activity Classification”,
    Indian Conference on Computer Vision, Graphics and Image processing (ICVGIP) 2010, pp. 178--182, Chennai, India, Dec. 2010.
    [abstract] [PDF] [BibTex]
    Abstract preview: This paper presents a novel descriptor for activity classification. The intuition behind the descriptor is "learning" statistics of optical flow histograms (as opposed to learning "raw& ... more
  13. Carter de Leo and B.S. Manjunath,
    “Multicamera video summarization from optimal reconstruction”,
    Tenth Asian Conference on Computer Vision, Queenstown, New Zealand, Nov. 2010.
    [abstract] [PDF] [BibTex]
    Abstract preview: We propose a principled approach to video summarization using optimal reconstruction as a metric to guide the creation of the summary output. The spatio-temporal video patches included in the summary ... more
  14. Zefeng Ni, Santhoshkumar Sunderrajan, Amir Rahimi, B. S. Manjunath,
    “Distributed Particle Filter Tracking With Online Multiple Instance Learning In a Camera Sensor Network”,
    IEEE International Conference on Image Processing, Sep. 2010.
    [abstract] [PDF] [BibTex]
    Abstract preview: This paper proposes a distributed algorithm for object tracking in a camera sensor network. At each camera node, an efficient online multiple instance learning algorithm is integrated with particle fi ... more
  15. Zefeng Ni, Santhoshkumar Sunderrajan, Amir Rahimi, B.S. Manjunath,
    “Particle Filter Tracking With Online Multiple Instance Learning”,
    IEEE International Conference on Pattern Recognition, Aug. 2010.
    [abstract] [PDF] [BibTex]
    Abstract preview: This paper addresses the problem of object tracking by learning a discriminative classifier to separate the object from its background. The online-learned classifier is used to adaptively model object ... more
  16. Thomas Kuo, Zefeng Ni, Carter De Leo, and B.S. Manjunath,
    “Design and Implementation of a Wide Area, Large-Scale Camera Network”,
    IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE Workshop on Camera Networks,, Jun. 2010.
    [abstract] [PDF] [BibTex]
    Abstract preview: We describe a wide area camera network on a campus setting, the SCALLOPSNet (Scalable Large Optical Sensor Network). It covers with about 100 stationary cameras an expansive area that can be divided i ... more
  17. Swapna Joshi, S. Karthikeyan, B. S. Manjunath, Scott Grafton and Kent A. Kiehl,
    “Anatomical Parts-Based Regression Using Non-Negative Matrix Factorization”,
    IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 2863-2870, Jun. 2010.
    [abstract] [PDF] [BibTex]
    Abstract preview: Non-negative matrix factorization (NMF) is an excellent tool for unsupervised parts-based learning, but proves to be ineffective when parts of a whole follow a specific pattern. Analyzing such local c ... more
  18. A.H.K. Roeder , V. Chickarmane, A.Cunha, B. Obara, B.S. Manjunath and E.M. Meyerowitz,
    “Variability in the Control of Cell Division Underlies Sepal Epidermal Patterning in Arabidopsis thaliana”,
    PLoS Biology, vol. 8, no. 5, pp. e1000367, May. 2010.
    [abstract] [PDF] [BibTex]
    Abstract preview: How growth and proliferation are precisely controlled in organs during development and how the regulation of cell division contributes to the formation of complex cell type patterns are important ques ... more
  19. Laura E. Boucheron, B. S. Manjunath, and Neal R. Harvey,
    “USE OF IMPERFECTLY SEGMENTED NUCLEI IN THE CLASSIFICATION OF HISTOPATHOLOGY IMAGES OF BREAST CANCER”,
    Proc. of IEEE ICASSP, pp. 666-699, Dallas, Texas, Mar. 2010.
    [abstract] [PDF] [BibTex]
    Abstract preview: Many features used in the analysis of pathology imagery are inspired by grading features defined by clinical pathologists as important for diagnosis and characterization. A large majority of these fea ... more
  20. Zefeng Ni, Dong Tian, Sitaram Bhagavathy, Joan Llach and B. S. Manjunath,
    “Improving The Quality of Depth Image Based Rendering for 3D Video Systems”,
    IEEE International Conference on Image Processing, 2009, pp. 513-516, Cairo, Egypt, Nov. 2009.
    [abstract] [PDF] [BibTex]
    Abstract preview: In 3D Video (3DV) applications, a reduced number of views plus depth maps are transmitted or stored. When there is a need to render virtual views in between the actual views, the technique of depth im ... more
  21. B. Gretarsson, J. O'Donovan, S. Bostandjiev and T. Hollerer,
    “WiGis: A Framework for Scalable Web-based Interactive Graph Visualizations”,
    17th International Symposium on Graph Drawing, Chicago, Il., Sep. 2009.
    [abstract] [PDF] [BibTex]
    Abstract preview:  
  22. J. O'Donovan, B. Gretarsson, S. Bostandjiev, T. Hollerer and B. Smyth,
    “A Visual Interface for Social Information Filtering”,
    International Conference on Social Computing, pp. 74–81, Vancouver, Canada, Aug. 2009.
    [abstract] [PDF] [BibTex]
  23. Michael James Quinn,
    “Toward Persistent Tracking and Identification in Camera Sensor Networks”,
    Ph.D. Thesis, University of California, Santa Barbara, Dec. 2008.
    [abstract] [PDF] [BibTex]
    Abstract preview: In recent years, research in the area of camera sensor networks has accelerated dramatically with the increased availability of cheap sensing, processing, and communications hardware. Design, implemen ... more
  24. Alphan Altinok, Erkan Kiris, Emre Sargin, Leslie Wilson, Stuart C. Feinstein, B.S. Manjunath and Kenneth Rose,
    “Quantification of dynamic behavior of microtubules in living cells using novel computational methods”,
    38th Annual Meeting of Society for Neuroscience (SfN), Washington, DC, USA, Nov. 2008.
    [abstract] [PDF] [BibTex]
    Abstract preview: Studies of MT dynamic instability in living cells require MT tip tracking, data analysis and calculation of dynamics statistics. Generally, these tasks are performed manually. Investigators manually f ... more
  25. E. Kiris, M. R. Gaylord, D. Ventimiglia, A. Altinok, M.E. Sargin, K. Rose, B.S. Manjunath, M. A. Jordan, L. Wilson and S. C. Feinstein,
    “Effects of tau pseudo-phosphorylation at residues thr231 ser262 ser396 and ser404 upon regulation of microtubule dynamic instability in living cells”,
    38th Annual Meeting of Society for Neuroscience (SfN), Washington, DC, USA, Nov. 2008.
    [abstract] [PDF] [BibTex]
    Abstract preview: Tau is a neural specific microtubule associated protein that is crucial for the proper development and maintenance of the nervous system. Mechanistically, tau binds directly to microtubules (MT), prom ... more
  26. M.E. Sargin, A. Altinok, K. Rose, B.S. Manjunath,
    “Conditional Iterative Decoding of Two Dimensional Hidden Markov Models”,
    Proc. IEEE International Conference on Image Processing, pp. 2552-2555, San Diego, CA, Oct. 2008.
    [abstract] [PDF] [BibTex]
    Abstract preview: Two Dimensional HiddenMarkovModels (2D-HMMs) provide substantial benefits for many computer vision and image analysis applications. Many fundamental image analysis problems, including segmentation and ... more
  27. M. Quinn, R. Mudumbai, T. Kuo, Z. Ni, C. De Leo and B. S. Manjunath,
    “VISNET: A Distributed Vision Testbed”,
    ACM/IEEE International Conference on Distributed Smart Cameras, 2008, pp. 364-371, Vienna, Sep. 2008.
    [abstract] [PDF] [BibTex]
    Abstract preview: We introduce UCSB�s Visual Sensor Network (VISNET) and discuss current research being conducted with the system. VISNET is a ten-node experimental camera network at UCSB used for various vision-r ... more
  28. Anindya Sarkar, Vishwakarma Singh, Pratim Ghosh, B. S. Manjunath, Ambuj Singh,
    “Duplicate Video Detection - Comparison of Proposed Distance Function with Dynamic Time Warping and Dependence of Detection Accuracy on Keyframe Selection”,
    VRL Technical Report, University of California, Santa Barbara, May. 2008.
    [abstract] [PDF] [BibTex]
    Abstract preview: The problem we are considering here is duplicate video detection. We have a database of N videos and we store compact signatures, called fingerprints, for each of them. When a query video is presented ... more
  29. M. E. Sargin, A. Altinok, K. Rose and B.S. Manjunath,
    “Deformable Trellis: Open Contour Tracking in Bio-Image Sequences”,
    IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP'08), Las Vegas, USA, Apr. 2008.
    [abstract] [PDF] [BibTex]
    Abstract preview: This paper presents an open contour tracking method that employs an arc-emission Hidden Markov Model (HMM). The algorithm encodes the shape information of the structure in a spatially deformable trell ... more
  30. A. Altinok, E. Sargin, E. Kiris, L. Wilson, S. C. Feinstein, B.S. Manjunath and K. Rose,
    “Segmenting filamentous biological structures by automated tracing”,
    Society for Neuroscience Annual Meeting (SfN), San Diego, CA, Nov. 2007.
    [abstract] [PDF] [BibTex]
    Abstract preview: Currently, biological image analysis generally relies on manual segmentation of objects and subsequent quantification of desired features. In the case of filamentous structures, such as cytoskeletal s ... more
  31. E. Kiris, M. R. Gaylord, J. Reifert, M.E. Sargin, A. Altinok, K. Rose, B.S. Manjunath, M. A. Jordan, L. Wilson and S. C. Feinstein,
    “Effects of combinatorial tau pseudophosphorylation upon microtubule binding assembly andthe regulation of dynamic instability in vitro”,
    Society for Neuroscience (SfN), San Diego, CA, USA, Nov. 2007.
    [abstract] [PDF] [BibTex]
    Abstract preview: Tau is a neural specific microtubule-associated protein that is crucial for the proper development and maintenance of the nervous system. Mechanistically, tau binds directly to microtubules, promotes ... more
  32. J. Kleban, A. Sarkar, E. Moxley, S. Mangiat, S. Joshi, T. Kuo and B.S. Manjunath,
    “Feature fusion and redundancy pruning for rush video summarization”,
    International Workshop on TRECVID Video Summarization, pp. 84-88, Augsburg, Bavaria, Germany, Sep. 2007.
    [abstract] [PDF] [BibTex]
    Abstract preview: This paper presents a video summarization technique for rushes that employs high-level feature fusion to identify segments for inclusion. It aims to capture distinct video events using a variety of fe ... more
  33. Vebjorn Ljosa and Ambuj K. Singh,
    “APLA: Indexing Arbitrary Probability Distributions”,
    23rd International Conference on Data Engineering (ICDE), pp. 946-955, Apr. 2007.
    [abstract] [PDF] [BibTex]
    Abstract preview: The ability to store and query uncertain information is of great benefit to databases that infer values from a set of observations, including databases of moving objects, sensor readings, historical b ... more
  34. Samuel Frame and S. Rao Jammalamadaka,
    “Generalized Mixture Models, Semi-supervised Learning, and Unknown Class Inference”,
    Advances in Data Analysis and Classification, Springer, 2007.
    [abstract] [PDF] [BibTex]
    Abstract preview: In this paper, we discuss Generalized Mixture Models and related Semi-supervised learning methods, and show how they can be used to provide explicit methods for unknown class inference. After a brief ... more
  35. T. Manna, G. Grenningloh, HP Miller, L. Wilson,
    “Stathmin Family Protein SCG10 Differentially Regulates the Plus and Minus ends Dynamics of Microtubules at Steady State in Vitro: Implications for its role in Neurite Outgrowth”,
    Biochemistry, vol. 46, pp. 3543-3552, 2007.
    [abstract] [BibTex]
  36. Vebjorn Ljosa and Ambuj K. Singh,
    “Top-k Spatial Joins of Probabilistic Objects”,
    Center for Bio-Image Informatics, University of California, Santa Barbara, 2007.
    [abstract] [BibTex]
  37. E. Kiris, M. Massie, A. Altinok, K. Rose, M.A. Jordan, L. Wilson and S.C. Feinstein,
    “Effects of tau pseudophosphorylation at residues ser262 ser396 andser404 upon microtubule binding and assembly in vitro”,
    American Society for Cell Biology (ASCB), San Diego, CA, USA, Dec. 2006.
    [abstract] [BibTex]
  38. Luca Bertelli, Baris Sumengen, B.S. Manjunath,
    “Redundancy in All Pairs Fast Marching Method”,
    IEEE International Conference on Image Processing 2006 (ICIP06), Atlanta, GA USA, Oct. 2006.
    [abstract] [PDF] [BibTex]
    Abstract preview: In this paper, we analyze the redundancy in calculating all pairs of geodesic distances on a rectangular grid. Fast marching method is an efficient way to estimate the geodesic distances from a point. ... more
  39. Dmitry Fedorov, Baris Sumengen and B. S. Manjunath,
    “Multi-Focus Imaging using Local Focus Estimation and Mosaicking”,
    IEEE International Conference on Image Processing 2006 (ICIP06), Atlanta, GA USA, Oct. 2006.
    [abstract] [PDF] [BibTex]
    Abstract preview: We propose an algorithm to generate one multi-focus image from a set of images acquired at different focus settings. First images are registered to avoid misalignment if needed. Then, best focus is es ... more
  40. Jiyun Byun, Mark R. Verardo, Baris Sumengen, Geoffrey P. Lewis, B. S. Manjunath and Steven K. Fisher,
    “Automated tool for the detection of cell nuclei in digital microscopic images: Application to retinal images”,
    Molecular Vision, vol. 12, pp. 949-960, http://www.molvis.org/molvis/v12/a107/, Aug. 2006.
    [abstract] [PDF] [BibTex]
    Abstract preview: Purpose: To develop an automated nuclei detection tool that provides reliable and consistently accurate results for counting cell nuclei. Methods: We propose a simple yet robust method to analyze lar ... more
  41. Alphan Altinok, Motaz El-Saban, Austin Peck, Leslie Wilson, Stuart Feinstein, B.S Manjunath and Kenneth Rose,
    “Activity Analysis in Microtubule Videos by Mixture of Hidden Markov Models”,
    International Conference on Computer Vision and Pattern Recognition (CVPR), New York, NY, Jun. 2006.
    [abstract] [PDF] [BibTex]
    Abstract preview: We present an automated method for the tracking and dynamics modeling of microtubules -a major component of the cytoskeleton- which provides researchers with a previously unattainable level of data an ... more
  42. Baris Sumengen, Luca Bertelli and B.S. Manjunath,
    “Fast and Adaptive Pairwise Similarities for Graph Cuts-based Image Segmentation”,
    IEEE CVPR Workshop on Perceptual Organization in Computer Vision (POCV), New York City, Jun. 2006.
    [abstract] [PDF] [BibTex]
    Abstract preview: We introduce the use of geodesic distances and geodesic radius for calculating pairwise similarities needed in various graph cuts based methods. By using geodesics on an edge strength function we are ... more
  43. Motaz El-Saban, Alphan Altinok, Austin Peck, Charles Kenney, Stuart Feinstein, Leslie Wilson, Kenneth Rose and B.S Manjunath,
    “Automated tracking and modeling of microtubule dynamics”,
    IEEE International Symposium on Biomedical Imaging (ISBI), Crystal City, CA, Apr. 2006.
    [abstract] [PDF] [BibTex]
    Abstract preview: The method of microtubule tracking and dynamics analysis, presented here, improves upon the current means of manual and automated quantification of microtubule behavior. Key contributions are increasi ... more
  44. M.R. Verardo, G.P. Lewis, M. Takeda, K.A. Linberg, U. Wilhelmsson, M. Pekny, D.F. Chen and S.K. Fisher,
    “Lack of Intermediate Filaments in GFAP -/-vim-/- Mice leads to Changes in Mueller Cell Endfeet and Ganglion Cells Following Retinal Detachment”,
    Invest Ophthalmol Vision Science 2006;47: Association for Research in Vision and Ophthalmology (ARVO) E-Abstract 4225, Fort Lauderdale, Florida, USA, Apr. 2006.
    [abstract] [PDF] [BibTex]
    Abstract preview: Purpose: An increase in the intermediate filament proteins GFAP and vimentin occurs in Mueller cells after retinal detachment in humans and in animal models. Here we sought to characterize changes in ... more
  45. S. K. Fisher, J. Byun, D. Fedorov, N. Vu, B. Sumengen, M. Verardo, G. P. Lewis and B. S. Manjunath,
    “Image Informatics Tools for the analysis of Retinal Images”,
    Invest Ophthalmol Vision Science 2006;47: Association for Research in Vision and Ophthalmology (ARVO) E-Abstract 4225, Fort Lauderdale, Florida, USA, Apr. 2006.
    [abstract] [PDF] [BibTex]
    Abstract preview: Purpose: To develop software tools that can be used for the enhancement and quantitative analysis of retinal images, and to test these methods on a large retinal image database. Methods: We have asse ... more
  46. B. S. Manjunath, B. Sumengen, Z. Bi, J. Byun, M. El-Saban, D. Fedorov and N. Vu,
    “Towards Automated Bioimage Analysis: From Features to Semantics”,
    IEEE International Symposium on Biomedical Imaging (ISBI), pp. 255-258, Crystal City, CA, Apr. 2006.
    [abstract] [PDF] [BibTex]
    Abstract preview: Recent advances in bio-molecular imaging have afforded biologists a more thorough understanding of cellular functions in complex tissue structures. For example, high resolution fluorescence images of ... more
  47. J. Byun, N. Vu, B. Sumengen and B. S. Manjunath,
    “Quantitative analysis of immunofluorescent retinal images”,
    IEEE International Symposium on Biomedical Imaging (ISBI), pp. 1268-1271, Crystal City, CA, Apr. 2006.
    [abstract] [PDF] [BibTex]
    Abstract preview: We present a novel method to quantitatively analyze confocal microscope images of retinas. We automatically detect nuclei within the outer nuclear layer (ONL) in a retinal image. Based on nuclei detec ... more
  48. Vebjorn Ljosa, Arnab Bhattacharya and Ambuj K. Singh,
    “LB-Index: A Multi-Resolution Index Structure for Images”,
    22nd International Conference on Data Engineering (ICDE), Apr. 2006.
    [abstract] [PDF] [BibTex]
    Abstract preview: In many domains, the similarity between two images depends on the spatial locations of their features. The earth mover's distance (EMD), first proposed by Werman et al. [8], measures such similar ... more
  49. Motaz El-Saban,
    “Automated Microtubule Tracking and Analysis”,
    Ph.D. Thesis, University of California, Santa Barbara, Mar. 2006.
    [abstract] [PDF] [BibTex]
    Abstract preview: Microtubules are major components of the cytoskeleton and play an important role in a number of cellular functions such as maintaining cell shape, cell division and transport of various molecules. Abn ... more
  50. Md. Aleemuddin Siddiqi and S. Rao Jammalamadaka,
    “Analysis of Microtubules using Growth Curve Modeling”,
    VRL, ECE, UCSB, Mar. 2006.
    [abstract] [PDF] [BibTex]
    Abstract preview: The activity of microtubules in cell structure has been of great importance in studying certain diseases and their treatments. For instance, promising anti-cancer drugs block cell division by stabiliz ... more
  51. Samuel J. Frame, S. Rao Jammalamadaka,
    “Semi-Supervised Learning and Generalized Mixture Models in the analysis of Retinal Images”,
    Center for Bio-Image Informatics, UCSB, Mar. 2006.
    [abstract] [PDF] [BibTex]
    Abstract preview: The Bio-Image Informatics research program at UCSB is a collaborative effort funded by the National Science Foundation. The statistical computing problem we address in this paper is to tailor an appli ... more
  52. Vebjorn Ljosa, Arnab Bhattacharya and Ambuj K. Singh,
    “Indexing Spatially Sensitive Distance Measures Using Multi-Resolution Lower Bounds”,
    10th International Conference on Extending Database Technology (EDBT), Mar. 2006.
    [abstract] [PDF] [BibTex]
    Abstract preview: Comparison of images requires a distance metric that is sensitive to the spatial location of objects and features. Such sensitive distance measures can, however, be computationally infeasible due to t ... more
  53. Tapas Manna, Douglas Thrower, Herbert P. Miller, Patrick Curmi and Leslie Wilson,
    “Stathmin Strongly Increases the Minus End Catastrophe Frequency and Induces Rapid Treadmilling of Bovine Brain Microtubules at Steady State in Vitro”,
    The Journal of Biological Chemistry, vol. 281, no. 4, pp. 2071–2078, Jan. 2006.
    [abstract] [PDF] [BibTex]
    Abstract preview: Stathmin is a ubiquitous microtubule destabilizing protein that is believed to play an important role linking cell signaling to the regulation of microtubule dynamics. Here we show that stathmin stron ... more
  54. Automated Microtubule Tracking and Analysis,
    “A. Altinok, E. Kiris, B.S. Manjunath, L. Wilson, S. C. Feinstein, K. Rose”,
    46th Annual Meeting of the American Society for Cell Biology, San Diego, CA, 2006.
    [abstract] [BibTex]
  55. Alphan Altinok, Austin Peck and Kenneth Rose,
    “Computational Methods for Analyzing Patterns in Dynamic”,
    Biological Phenomena: An Application to Microtubule Dynamics, 2006.
    [abstract] [PDF] [BibTex]
    Abstract preview: Live cell imaging technologies have advanced enormously over the past decade. However, in most cases, analysis remains a painstaking, tedious and largely manual task, limiting the quantity and quality ... more
  56. Alphan Altinok, Baris Sumengen, B.S Manjunath and Kenneth Rose,
    “Reducing incidental fluorescence in live cell imaging”,
    ECE, UCSB, 2006.
    [abstract] [PDF] [BibTex]
    Abstract preview: Fluorescence staining is the prevailing image acquisition technique in cell biology research. A problem of this method is the incidental fluorescence, that is the total fluorescence collected by a cam ... more
  57. Zhiqiang Bi and B.S. Manjunath,
    “Analysis Of Confocal Microscope Images From Retina Detachment Experiments Using Texture Bases Features”,
    VRL, ECE, UCSB, 2006.
    [abstract] [PDF] [BibTex]
    Abstract preview: Retinal detachment, the separation of retina from retinal pigmented epithelium, causes changes to many types of cells in retinal tissue. A successful modeling of these changes can help to understand t ... more
  58. Janis M. Bunker, Kathy Kamath, Leslie Wilson, Mary Ann Jordan, and Stuart C. Feinstein,
    “Ftdp-17 Mutations Compromise the Ability of Tau to Regulate Microtubule Dynamics In Cells”,
    The Journal of Biological Chemistry, 2006.
    [abstract] [PDF] [BibTex]
    Abstract preview: The neural microtubule-associated protein tau binds directly to microtubules and regulates their dynamic behavior. In addition to being required for normal development, maintenance and function of the ... more
  59. Dmitry Fedorov, Baris Sumengen and B. S. Manjunath,
    “Tile-based framework for local enhancement of bio imagery”,
    VRL, ECE, UCSB, Dec. 2005.
    [abstract] [PDF] [BibTex]
    Abstract preview: We present a simple framework for image enhancement using local image information. The main idea is to divide the image into small tiles and individually enhance each of these tiles. Enhanced tiles ar ... more
  60. Arnab Bhattacharya, Vebjorn Ljosa, Jia-Yu Pan, Mark R. Verardo, Hyungjeong Yang, Christos Faloutsos and Ambuj K. Singh,
    “ViVo: Visual vocabulary construction for mining biomedical images”,
    Fifth IEEE International Conference on Data Mining (ICDM), pp. 50-57, Nov. 2005.
    [abstract] [PDF] [BibTex]
    Abstract preview: Given a large collection of medical images of several conditions and treatments, how can we succinctly describe the characteristics of each setting? For example, given a large collection of retinal im ... more
  61. Robert John Coulier,
    “A Storage, Processing, and Retrieval System for Microtubule Tracking Data”,
    IEEE Computational Systems Bioinformatics Conference, Stanford University, CA, Aug. 2005.
    [abstract] [PDF] [BibTex]
    Abstract preview: Given a set of cell microtubule images taken at regular time intervals, individual microtubule positions can be tracked over time. This position data can then be analyzed to obtain event information f ... more
  62. Ambuj K. Singh, Arnab Bhattacharya and Vebjorn Ljosa,
    “Current Challenges in Bioimage Database Design”,
    International Workshop on Bioimage Data Mining and Informatics, pp. 375-379, IEEE Computational Systems Bioinformatics Conference (CSB), Aug. 2005.
    [abstract] [PDF] [BibTex]
    Abstract preview: Information technology research has played a significant role in the high-throughput acquisition and analysis of biological information. The tremendous amount of information gathered from genomics in ... more
  63. M. A. El Saban and B. S. Manjunath,
    “Spatiotemporal Contour Tracking of Microtubules”,
    VRL, ECE, UCSB, Jun. 2005.
    [abstract] [PDF] [BibTex]
    Abstract preview: Microtubules (MTs), one of three major cytoskeletal components, serve numerous critical functions in cells. Mechanistically, MTs are not static polymers; rather, they can be very dynamic and their pre ... more
  64. M. A. El Saban and B. S. Manjunath,
    “Tracking curvilinear structures using active contours and application to microtubule videos”,
    VRL, ECE, UCSB, Jun. 2005.
    [abstract] [PDF] [BibTex]
    Abstract preview: We present a novel active contour-based tracking algorithm for highly deformable and fast moving curvilinear structures. We propose to use line features as external forces for the active contour for t ... more
  65. A. Altinok, A. J. Peck, S. C. Feinstein, L. Wilson, B. S. Manjunath and K. Rose,
    “Automated Motion Detection and Quantitation of Cell Components: Application to Dynamic Populations of Microtubules in Living Cells”,
    45th Annual Meeting of the American Society for Cell Biology, San Francisco, CA, 2005.
    [abstract] [BibTex]
  66. Steven K. Fisher, Geoffrey P. Lewis, Kenneth A. Linberg and Mark R. Verardo,
    “Cellular remodeling in mammalian retina: results from studies of experimental retinal detachment”,
    Progress in Retinal and Eye Research, vol. 25, pp. 395-431, 2005.
    [abstract] [PDF] [BibTex]
    Abstract preview: Retinal detachment, the separation ofthe neural retina from the retinal pigmented epithelium, starts a cascade ofevents that results in cellular changes throughout the retina. While the degeneration o ... more
  67. M.R. Verardo, G.P. Lewis, M. Takeda, K.A. Linberg, B. Wardak and M. Rabena,
    “Retinal Detachment in Mice Deficient in GFAP and Vimentin: Reduced Glial Hypertrophy and Increased Ganglion Cell Remodeling”,
    International Symposium on Neural Regeneration, 2005.
    [abstract] [PDF] [BibTex]
    Abstract preview: Retinal detachment induces Muller glia cell (MC) hypertrophy. Structural and immunolabeling data suggest a prominent role for the intermediate filament cytoskeleton in this process. There also may be ... more
  68. M.R. Verardo, G.P. Lewis, M. Takeda, B.M. Wardak, M.D. Rabena, D.F. Chen, S.K. Fisher,
    “Glial Hypertrophy and Neuronal Remodeling in Mice Deficient in GFAP and Vimentin Following Experimental Retinal Detachment”,
    Invest Ophthalmol Vision Science 2004;45: Association for Research in Vision and Ophthalmology (ARVO) E-Abstract 3000, Fort Lauderdale, Florida, USA, 2005.
    [abstract] [PDF] [BibTex]
    Abstract preview: Purpose: Retinal detachment induces Muller cell hypertrophy both within the retina and as cellular membranes in the subretinal space. Structural and immunolabeling data suggest a prominent role for th ... more
  69. Xinding Sun,
    “Motion Activity for Video Indexing”,
    Ph.D. Thesis, University of California, Santa Barbara, Jun. 2004.
    [abstract] [PDF] [BibTex]
    Abstract preview: Video indexing based on motion is an emerging research area. While most previous work focused on video indexing using motion vectors, a detailed quantitative characterization of the spatial and tempor ... more
  70. Xinding Sun, Jonathan Foote, Don Kimber, B. S. Manjunath,
    “Region of Interest Extraction and Virtual Camera Control Based on Panoramic Video Capturing”,
    IEEE Transactions on Multimedia, 2004.
    [abstract] [PDF] [BibTex]
    Abstract preview: We present a system for automatically extracting the region of interest and controlling virtual cameras control based on panoramic video. It targets applications such as classroom lectures and video c ... more
  71. X. Sun, and B. S. Manjunath,
    “Panoramic Capturing and Recognition of Human activity”,
    IEEE International Conference on Image Processing (ICIP), vol. 2, pp. 813-816, Rochester, NY, USA, Sep. 2002.
    [abstract] [PDF] [BibTex]
    Abstract preview: This paper presents a unified approach to human activity capturing and recognition. It targets applications such as a speaker walking, turning around, sitting and getting up from a chair in a classroo ... more
  72. X. Sun, B. S. Manjunath, and A. Divakaran,
    “Representation of motion activity in hierarchical levels for video indexing and filtering”,
    IEEE International Conference on Image Processing (ICIP), vol. 1, pp. 149-152, Rochester, NY, USA, Sep. 2002.
    [abstract] [PDF] [BibTex]
    Abstract preview: A method for video indexing and filtering based on motion activity characteristics in hierarchical levels is proposed. To extract motion activity information, an MPEG (MPEG-1/2) video is first adaptiv ... more
  73. X. Sun, D. Kimber, J. Foote, and B. S. Manjunath,
    “Detecting Path Intersections in Panoramic Video”,
    IEEE International Conference on Multimedia and Expo (ICME), vol. 2, pp. 529-532, Lausanne, Switzerland, Aug. 2002.
    [abstract] [PDF] [BibTex]
    Abstract preview: Given panoramic video taken along a self-intersecting path, we present a method for detecting the intersection points. This allows "virtual tours" to be synthesized by splicing the panoramic ... more
  74. X. Sun, C.-W. Chen, and B. S. Manjunath,
    “Probabilistic Motion Parameter Models for Human Activity Recognition”,
    IEEE International Conference on Pattern Recognition (ICPR) 2002, vol. 1, pp. 443-446, Québec City, Canada, Aug. 2002.
    [abstract] [PDF] [BibTex]
    Abstract preview: A novel method for human activity recognition is presented. Given a video sequence containing human activity, the motion parameters of each frame are first computed using different motion parameter mo ... more
  75. X. Sun, J. Foote, D. Kimber, and B. S. Manjunath,
    “Panoramic Video Capturing and Compressed Domain Virtual Camera Control”,
    ACM International Multimedia Conference (MM '01), pp. 329-347, Ottawa, Canada, Oct. 2001.
    [abstract] [PDF] [BibTex]
    Abstract preview: A system for capturing panoramic video and a novel method for corresponding compressed domain virtual camera control is presented. It targets applications such as classroom lectures and video conferen ... more
  76. X. Sun, A. Divakaran, B. S. Manjunath,
    “A Motion Activity Descriptor and Its Extraction in Compressed Domain”,
    IEEE Pacific-Rim Conference on Multimedia (PCM '01), pp. 450-457, Beijing, China, Oct. 2001.
    [abstract] [PDF] [BibTex]
    Abstract preview: A novel motion activity descriptor and its extraction from a compressed MPEG (MPEG-1/2) video stream are presented. The descriptor consists of two parts, a temporal descriptor and a spatial descriptor ... more
  77. X. Sun, J. Foote, D. Kimber, and B. S. Manunath,
    “Recording the region of interest from FLYCAM panoramic video”,
    IEEE International Conference on Image Processing (ICIP 2001), pp. 409-412, Thessaloniki, Greece, Oct. 2001.
    [abstract] [PDF] [BibTex]
    Abstract preview: A novel method for region of interest tracking and recording video is presented. The proposed method is based on the FlyCam system 4, which produces high resolution and wide-angle video sequences by s ... more
  78. N. Strobel, S. K. Mitra and B. S. Manjunath,
    “Reversible wavelet and spectral transforms for lossless compression of color images”,
    IEEE Intl. Conference on Image Processing (ICIP'98), vol. 3, pp. 896-900, Chicago, IL, Oct. 1998.
    [abstract] [PDF] [BibTex]
    Abstract preview: A new lossless image compression method for progressive-resolution transmission of color images is proposed. It is based on spatial and spectral transforms. Reversible wavelet transforms are performed ... more
  79. Qinfen Zheng, R. Chellappa and B. S. Manjunath,
    “Balloon motion estimation using two frames”,
    25th Asilomar Conference on Signals, Systems and Computers, pp. 1057-1061, San Jose, CA, Oct. 1991.
    [abstract] [PDF] [BibTex]
    Abstract preview: A computational vision approach is presented for the estimation of 2-D translation, rotation, and scale from two partially overlapping images. An illuminant direction estimation method is first used ... more

Action Detection, Camera Networks and Multi-Modal Data

  1. de Melo Celso, Rothrock Brandon, Gurram Prudhvi, Ulutan Oytun, Manjunath B.S.,
    “Robot Control Gestures (RoCoG)”,
    Sep. 2020.
    [abstract] [PDF] [BibTex]
    Abstract preview: Building successful collaboration between humans and robots requires efficient, effective, and natural communication. This dataset supports the study of RGB-based deep learning model ... more
  2. O. Ulutan, A.S.M. Iftekhar, B.S. Manjunath,
    “VSGNet: Spatial Attention Network for Detecting Human-Object Interactions using Graph Convolutions”,
    CVPR 2020, Seattle , Jun. 2020.
    [abstract] [PDF] [BibTex]
    Abstract preview: Comprehensive visual understanding requires detection frameworks that can effectively learn and utilize object interactions while analyzing objects individually. This is the main objective in Human-Ob ... more
  3. Oytun Ulutan, Swati Rallapalli, Mudhakar Srivatsa, B.S. Manjunath,
    “Actor Conditioned Attention Maps for Video Action Detection”,
    The IEEE Winter Conference on Applications of Computer Vision,2020,527--536, Colorado, USA, Jan. 2020.
    [abstract] [PDF] [BibTex]
    Abstract preview: While observing complex events with multiple actors, humans do not assess each actor separately, but infer from the context. The surrounding context provides essential information for understanding ac ... more
  4. C. Torres, J. C. Fried, K. Rose and B. S. Manjunath,
    “A Multiview Multimodal System for Monitoring Patient Sleep”,
    IEEE Tran. Multimedia, May. 2018.
    [abstract] [PDF] [BibTex]
    Abstract preview: Clinical observations indicate that during critical care at the hospitals, a patient's sleep positioning and motion have a significant effect on recovery rate. Unfortunately, there is no formal m ... more
  5. Hang Qiu, Xiaochen Liu, Swati Rallapalli, Archith J. Bency, Rahul Urgaonkar, B.S. Manjunath, Ramesh Govindan, Kevin Chan,
    “KESTREL: Video Analytics for Augmented Multi-Camera Vehicle Tracking”,
    The Proceedings of ACM/IEEE International Conference on Internet-of-Things Design and Implementation (IoTDI), Orlando, Florida, Apr. 2018.
    [abstract] [PDF] [BibTex]
    Abstract preview: As mobile devices have become more powerful and GPU-equipped,vision-based applications are becoming feasible on these devices. Mobile devices can augment fixed camera surveillance systems to improve c ... more
  6. Oytun Ulutan, Benjamin Riggan, Nasser Nasrabadi, B.S. Manjunath,
    “A Bilinear Model for Person Detection in Multi-Modal Data”,
    IEEE Winter Conf. on Applications of Computer Vision (WACV 2018), March 12-14, 2018, Lake Tahoe, NV/CA, Lake Tahoe, CA, Mar. 2018.
    [abstract] [PDF] [BibTex]
    Abstract preview: We propose a bilinear model for processing multimodal data using a deep neural network architecture. The  multimodal data includes low resolution videos and associated seismic sensor time seq ... more
  7. Carlos Torres, Archith J. Bency, Jeffrey C. Fried, B. S. Manjunath,
    “RAM: Role Representation and Identification from combined Appearance and Activity Maps”,
    Proc. 11th International Conference on Distributed Smart Cameras, Stanford, California, Sep. 2017.
    [abstract] [PDF] [BibTex]
    Abstract preview: ThŒis work introduces a multimodal multiview camera network for role identi€cation and re-identi€cation in an Intensive Care Unit (ICU) room, where identifying individuals is not permittŠed. ŒThe ... more
  8. Archith John Bency, S. Karthikeyan, Carter De Leo, Santhoshkumar Sunderrajan, and B. S. Manjunath,
    “Search Tracker: Human-derived object tracking in-the-wild through large-scale search and retrieval”,
    IEEE Transactions Circuits and Systems for Video Technology, vol. 27, no. 8, pp. 1803-14, Aug. 2017.
    [abstract] [PDF] [BibTex]
    Abstract preview: Humans use context and scene knowledge to easily localize moving objects in conditions of complex illumination changes, scene clutter and occlusions. In this paper, we present a method to leverage hum ... more
  9. Carlos Torres, Jeffrey C. Fried, Kenneth Rose, B. S. Manjunath,
    “Deep Eye-CU (DECU): Summarization of Patient Motion in the ICU”,
    ECCV 2016 Workshop on Assistive Computer Vision and Robotics, pp. 178-194, Amsterdam, Netherlands, Oct. 2016.
    [abstract] [PDF] [BibTex]
    Abstract preview: Healthcare professionals speculate about the effects of poses and pose manipulation in healthcare. Anecdotal observations indicate that patient poses and motion affect recovery. Motion analysis using ... more
  10. Raghu Ganti, Mudhakar Srivatsa, B.S. Manjunath,
    “Entity reconciliation in a multi-camera network”,
    Proceedings of the 17th ACM International Conference on Distributed Computing and Networking (ICDCN'16), Singapore, Jan. 2016.
    [abstract] [PDF] [BibTex]
    Abstract preview: Location traces are becoming fairly abundant with the introduction of various mobile devices such as smartphones, in-car navigation units, and video cameras. Each individual type of device generates d ... more
  11. S. Sunderrajan and B. S. Manjunath,
    “Context-aware hypergraph modeling for re-identification and summarization”,
    IEEE Transactions on Multimedia, vol. 18, pp. 51-63, Jan. 2016.
    [abstract] [PDF] [BibTex]
    Abstract preview: Tracking and re-identification in wide-area camera networks is a challenging problem due to non-overlapping visual fields, varying imaging conditions, and appearance changes. We consider the problem o ... more
  12. Carlos Torres, Scott D. Hammond, Jeffrey C. Fried, B. S. Manjunath,
    “Sleep Pose Recognition in an ICU Using Multimodal Data and Environmental Feedback”,
    International Conference on Computer Vision Systems, vol. 9163, pp. 56-66, Copenhagen, Denmark, Jun. 2015.
    [abstract] [PDF] [BibTex]
    Abstract preview: Clinical evidence suggests that sleep pose analysis can shed light onto patient recovery rates and responses to therapies. In this work, we introduce a formulation that combines features from multimod ... more

BIO, Bio-Image Informatics and BISQUE

  1. Enrique Alegre, MT Garcia-Ordas, Victor Gonzalez-Castro, S Karthikeyan,
    “Vitality assessment of boar sperm using NCSR texture descriptor in digital images”,
    Sep. 2012.
    [abstract] [PDF] [BibTex]
    Abstract preview: Two new textural descriptor, named N Concentric Squares Resized (NCSR) and N Concentric Squares Resized (NCSH), have been proposed. These descriptors were used to classify 472 images of alive spermato ... more

BIO

  1. Panuakdet Suwannatat, Gabriel Luna, Geoffrey P. Lewis, Steven K. Fisher and Tobias Hollerer,
    “Scalable Interactive Analysis of Retinal Astrocyte Networks”,
    BioVis, 2012.
    [abstract] [BibTex]
    Abstract preview: Retinal astrocytes are one of two types of glial cells found in the mammalian retina. In mice, these highly planar cells are located in the innermost retinal layer termed the nerve fiber layer. We are ... more
  2. Sarit Y. Lesnik Oberstein, Jiyun Byun, Diego Herrera, Ethan A. Chapin, Steven K. Fisher, Geoffrey P. Lewis,
    “Cell proliferation in human epiretinal membranes: characterization of cell types and correlation with disease condition and duration”,
    Molecular Vision, vol. 17, pp. 1794-1805, Jul. 2011.
    [abstract] [PDF] [BibTex]
    Abstract preview: Purpose: To quantify the extent of cellular proliferation and immunohistochemically characterize the proliferating cell types in epiretinal membranes (ERMs) from four different conditions: proliferati ... more
  3. Alphan Altinok, B. S. Manjunath and Kenneth Rose,
    “Extracting Dynamic Microtubule Features from Image Sequences”,
    Asilomar Conference On Signals, Systems and Computers (ACSSC), Monterey, CA, Nov. 2007.
    [abstract] [PDF] [BibTex]
    Abstract preview: Microtubules (MT) are filamentous cytoskeletal structures composed of tubulin protein subunits. Through their dynamic behaviors, they participate in many essential cellular functions. MT dynamics are ... more
  4. Alphan Altinok, Erkan Kiris, Austin Peck, Stuart Feinstein, Leslie Wilson, B. S. Manjunath and Kenneth Rose,
    “Model based dynamics analysis in live cell microtubule images”,
    BMC Cell Biology, vol. 8, BioMed Central, Jul. 2007.
    [abstract] [PDF] [BibTex]
    Abstract preview: Background: The dynamic growing and shortening behaviors of microtubules are central to the fundamental roles played by microtubules in essentially all eukaryotic cells. Traditionally, microtubule beh ... more

Bio-Image Informatics and BISQUE

  1. Po-Yu Kao, Shailja, Jiaxiang Jiang, Angela Zhang, Amil Khan, Jefferson W Chen, BS Manjunath,
    “Improving Patch-Based Convolutional Neural Networks for MRI Brain Tumor Segmentation by Leveraging Location Information”,
    Frontiers in Neuroscience, Mar. 2020.
    [abstract] [PDF] [BibTex]
    Abstract preview: The manual brain tumor annotation process is time consuming and resource consuming, therefore, an automated and accurate brain tumor segmentation tool is greatly in demand. In this paper, we introduce ... more
  2. Jiaxiang Jiang, Po-Yu Kao, S. A. Belteton, D. B. Szymanski, B. S. Manjunath,
    “Accurate 3D Cell Segmentation Using Deep Feature and CRF Refinement”,
    IEEE International Conference on Image Processing (ICIP) 2019, Sep. 2019.
    [abstract] [PDF] [BibTex]
    Abstract preview: We consider the problem of accurately identifying cell boundaries and labeling individual cells in confocal microscopy images, specifically, 3D image stacks of cells with tagged cell membranes. Precis ... more
  3. Jiaxiang Jiang, Po-Yu Kao, Samuel A. Belteton, Daniel B. Szymanski, B.S. Manjunath,
    “Accurate 3D Cell Segmentation using Deep Feature and CRF Refinement”,
    ICIP 2019, Taipei, Taiwan, Sep. 2019.
    [abstract] [PDF] [BibTex]
    Abstract preview: We consider the problem of accurately identifying cell boundaries and labeling individual cells in confocal microscopy images, specifically, 3D image stacks of cells with tagged cell membranes. Precis ... more
  4. Dmitry Fedorov, B.S. Manjunath, Christian Lang, Kristiam Kvilekval,
    “Scalable Image Informatics”,
    Academic Press Library in Signal Processing, vol. 6, no. Chapter 9, Sep. 2017.
    [abstract] [PDF] [BibTex]
    Abstract preview: Images and video play a major role in scientific discoveries. Significant new advances in imaging science over the past two decades have resulted in new devices and technologies that are able to probe ... more

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