Publications

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Ph.D. THESIS

Batch Mode Active Learning for Multimedia Pattern Recognition“, School of Computing, Informatics and Decision Systems Engineering, Arizona State University, April 2013

 

PATENTS

S. Chakraborty, O. Tickoo, R. Iyer, “Method, Apparatus and System for Online Video Summarization”, US Provisional Patent Application 14/477,595 (patent pending)

 

JOURNALS / BOOK CHAPTERS / MAGAZINE ARTICLES

S. Panchanathan, M. Moore, H. Venkateswara, S. Chakraborty, T. McDaniel, “Computer Vision for Augmentative and Alternative Communication“, Computer Vision for Assistive Healthcare, Elsevier, 2018

H. Venkateswara, S. Chakraborty, S. Panchanathan, “Deep Learning Systems for Domain Adaptation in Computer Vision“, IEEE Signal Processing Magazine (SPM), Special Issue on Deep Learning for Visual Understanding, 2017

S. Panchanathan, S. Chakraborty, T. McDaniel et al., “Enriching the Fan Experience in a Smart Stadium Using Internet of Things Technologies“, International Journal of Semantic Computing (IJSC), 2017 (Special Issue on Best of IEEE ISM 2016)

S. Panchanathan, S. Chakraborty, T. McDaniel, R. Tadayon, “Person-Centered Multimedia Computing: A New Paradigm Inspired by Assistive and Rehabilitative Applications“, IEEE Multimedia Magazine (MM), 2016 (2017 IEEE Multimedia Best Department Article Award)

S. Panchanathan, S. Chakraborty, T. McDaniel, “Social Interaction Assistant: A Person-Centered Approach to Enrich Social Interactions for Individuals with Visual Impairments“, IEEE Journal on Selected Topics in Signal Processing (J-STSP), 2016

S. Chakraborty, V. Balasubramanian, Q. Sun, S. Panchanathan, J. Ye, “Active Batch Selection via Convex Relaxations with Guaranteed Solution Bounds“, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2015

S. Chakraborty, V. Balasubramanian, S. Panchanathan, “Adaptive Batch Mode Active Learning“, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2015

V. Balasubramanian, S. Chakraborty, S. Panchanathan, “Conformal Predictions for Information Fusion: A Comparative Study of P-Value Combination Methods“, Annals of Mathematics and Artificial Intelligence (AMAI), 2014

V. Balasubramanian, S. Chakraborty, S.S. Ho, H. Wechsler, S. Panchanathan, “Active Learning using Conformal Predictions“, Morgan Kaufmann Publ. (Elsevier), 2014

S. Chakraborty, V. Balasubramanian, S. Panchanathan, “Generalized Batch Mode Active Learning for Face-based Biometric Recognition“, Pattern Recognition Journal, 2012

S. Marcel, C. McCool, S. Chakraborty, V. Balasubramanian, S. Panchanathan et al. “On the Results of the First Mobile Biometry (MOBIO) Face and Speaker Verification Evaluation“, Lecture Notes on Computer Science (LNCS), 2010

 

CONFERENCES AND WORKSHOPS

A. Bhattacharya, S. Chakraborty, “Active Learning with n-ary Queries for Image Recognition“, IEEE Winter Conference on Applications of Computer Vision (WACV), 2019

V. Torvi, A. Bhattacharya, S. Chakraborty, “Deep Domain Adaptation to Predict Freezing of Gait in Patients with Parkinson’s Disease”, IEEE International Conference on Machine Learning and Applications (ICMLA), 2018

H. Ranganathan, H. Venkateswara, S. Chakraborty, S. Panchanathan, “Multi-Label Deep Active Learning with Label Correlation”, IEEE International Conference on Image Processing (ICIP), 2018

S. Chakraborty, Distributed Active Learning for Image Recognition“, IEEE Winter Conference on Applications of Computer Vision (WACV), 2018

S. Chakraborty, J. Stokes, L. Xiao, D. Zhou, M. Marinescu, A. Thomas, “Hierarchical Learning for Automated Malware Classification“, IEEE Military Communications Conference (MILCOM), 2017

H. Ranganathan, H. Venkateswara, S. Chakraborty, S. Panchanathan, “Deep Active Learning for Image Classification“, IEEE International Conference on Image Processing (ICIP), 2017

H. Venkateswara, J. Eusebio, S. Chakraborty, S. Panchanathan, “Deep Hashing Network for Unsupervised Domain Adaptation“, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017

H. Venkateswara, S. Chakraborty, T. McDaniel, S. Panchanathan, “Model Selection with Nonlinear Embedding for Unsupervised Domain Adaptation“, Workshop on Knowledge-based Techniques for Problem Solving and Reasoning (KnowPros) at the Association for the Advancement of Artificial Intelligence (AAAI), 2017

S. Panchanathan, S. Chakraborty, T. McDaniel et al. “Smart Stadium for Smart Living: Enriching the Fan Experience“, IEEE International Symposium on Multimedia (ISM), 2016 (Invited Paper)

H. Venkateswara, S. Chakraborty, S. Panchanathan, “Nonlinear Embedding Transform for Unsupervised Domain Adaptation“, Workshop on Transferring and Adapting Source Knowledge in Computer Vision (TASK-CV) at the European Conference on Computer Vision (ECCV), 2016

H. Ranganathan, S. Chakraborty, S. Panchanathan, “Transfer of Multi-modal Emotion Features ion Deep Belief Networks“, Asilomar Conference on Signals, Systems and Computers, 2016

H. Ranganathan, S. Chakraborty, S. Panchanathan, “Multi-modal Emotion Recognition using Deep Learning Architectures“, IEEE Winter Conference on Applications of Computer Vision (WACV), 2016

S. Chakraborty, O. Tickoo, R. Iyer, “Towards Distributed Video Summarization“, ACM Multimedia Conference (ACM-MM), 2015

S. Chakraborty, V. Balasubramanian, A. Ravi Sankar, S. Panchanathan, J. Ye, “BatchRank: A Novel Batch Mode Active Learning Framework for Hierarchical Classification“, ACM Conference on Knowledge Discovery and Data Mining (KDD), 2015

S. Chakraborty, O. Tickoo, R. Iyer, “Adaptive Keyframe Selection for Video Summarization“, IEEE Winter Conference on Applications of Computer Vision (WACV), 2015

S. Chakraborty, J. Zhou, V. Balasubramanian, S. Panchanathan, I. Davidson, J. Ye, “Active Matrix Completion“, IEEE International Conference on Data Mining (ICDM), 2013

S. Chakraborty, H. Venkateswara, V. Balasubramanian, S. Panchanathan, “Active Batch Selection for Fuzzy Classification in Facial Expression Recognition“, IEEE International Conference on Machine Learning and Applications (ICMLA), 2011

R. Chattopadhyay, S. Chakraborty, V. Balasubramanian, S. Panchanathan, “Optimization-based Domain Adaptation towards Person-Adaptive Classification Models“, IEEE International Conference on Machine Learning and Applications (ICMLA), 2011

S. Chakraborty, V. Balasubramanian, S. Panchanathan, “Optimal Batch Selection for Active Learning in Multi-label Classification“, ACM Multimedia Conference (ACM-MM), 2011

S. Chakraborty, V. Balasubramanian, S. Panchanathan, “Dynamic Batch Mode Active Learning“, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011

S. Chakraborty, V. Balasubramanian, S. Panchanathan, “An Optimization Based Framework for Dynamic Batch Mode Active Learning“, Workshop on Optimization for Machine Learning at Neural Information Processing Systems (NIPS), 2010

V. Balasubramanian, S. Chakraborty, S. Krishna, S. Panchanathan, “Enhancing Social Interactions of Individuals with Visual Impairments: A Case Study for Assistive Machine Learning“, Workshop on Machine Learning for Assistive Technologies at Neural Information Processing Systems (NIPS), 2010

V. Balasubramanian, S. Chakraborty, S. Panchanathan, “Multiple Kernel Learning for Efficient Conformal Predictions“, Workshop on New Directions in Multiple Kernel Learning at Neural Information Processing Systems (NIPS), 2010

S. Chakraborty, V. Balasubramanian, S. Panchanathan, “Dynamic Batch Size Selection for Batch Mode Active Learning in Biometrics“, IEEE International Conference on Machine Learning and Applications (ICMLA) 2010

V. Balasubramanian, J. Ye, S. Chakraborty, S. Panchanathan, “Kernel Learning for Efficiency Maximization in the Conformal Predictions Framework“, IEEE International Conference on Machine Learning and Applications (ICMLA) 2010

S. Chakraborty, V. Balasubramanian, S. Panchanathan, “Learning from Summaries of Videos: Applying Batch Mode Active Learning to Face-based Biometrics“, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Workshop on Biometrics, 2010

S. Chakraborty, V. Balasubramanian, S. Panchanathan, “Batch Mode Active Learning for Biometric Recognition“, SPIE International Conference on Biometric Technology for Human Identification, SPIE Defense, Security & Sensing, 2010

V. Balasubramanian, S. Chakraborty, S. Krishna, S. Panchanathan, “Human-Centered Machine Learning in a Social Interaction Assistant for Individuals with Visual Impairments“, Symposium on Assistive Machine Learning for People with Disabilities at Neural Information Processing Systems (NIPS), 2009

V. Balasubramanian, S. Chakraborty, S. Panchanathan, “Online Active Learning using Conformal Predictions“, Workshop on Analysis and Design of Algorithms for Interactive Machine Learning at Neural Information Processing Systems (NIPS), 2009

V. Balasubramanian, S. Chakraborty, S. Panchanathan, “Generalized Query by Transduction for Online Active Learning“, IEEE International Conference on Computer Vision (ICCV), Workshop on Online Learning for Computer Vision, 2009

V. Balasubramanian, S. Chakraborty, S Panchanathan, “Multiple Cue Integration in Transductive Confidence Machines for Head Pose Classification“, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Workshop on Online Learning for Classification, 2008

G. Gupta, S.K. Saha, S. Chakraborty, C. Mazumdar, “Document Frauds: Identification and Linking Fake Documents to Scanners and Printers“, IEEE International Conference on Computing, Theory and Applications (ICCTA), 2007

 

TECHNICAL REPORTS

V. Balasubramanian, S. Chakraborty, S. Panchanathan, “Confidence Estimation in Pattern Classification: An Analysis with Head Pose Estimation“, Technical Report TR-09-12, School of Computing, Informatics and Decision Systems Engineering, Arizona State University, 2009