| Feature Extraction and Learning for Visual Data PS Chandakkar, R Venkatesan, B Li Feature Engineering for Machine Learning and Data Analytics, 55-85, 2018 | 362* | 2018 |
| Classification of Diabetic Retinopathy Images Using Multi-Class Multiple-Instance Learning Based on Color Correlogram Features R Venkatesan, P Chandakkar, B Li, HK Li | 62* | |
| Strategies for re-training a pruned neural network in an edge computing paradigm PS Chandakkar, Y Li, PLK Ding, B Li 2017 IEEE International Conference on Edge Computing (EDGE), 244-247, 2017 | 49 | 2017 |
| Simpler non-parametric methods provide as good or better results to multiple-instance learning R Venkatesan, P Chandakkar, B Li Proceedings of the IEEE International Conference on Computer Vision, 2605-2613, 2015 | 26 | 2015 |
| Retrieving clinically relevant diabetic retinopathy images using a multi-class multiple-instance framework PS Chandakkar, R Venkatesan, B Li Medical Imaging 2013: Computer-Aided Diagnosis 8670, 182-191, 2013 | 16 | 2013 |
| Supporting navigation of outdoor shopping complexes for visuallyimpaired users through multi-modal data fusion A Paladugu, PS Chandakkar, P Zhang, B Li 2013 IEEE International Conference on Multimedia and Expo (ICME), 1-7, 2013 | 10 | 2013 |
| A computational approach to relative aesthetics V Gattupalli, PS Chandakkar, B Li 2016 23rd International Conference on Pattern Recognition (ICPR), 2446-2451, 2016 | 8* | 2016 |
| Distributed learning of deep feature embeddings for visual recognition tasks B Bhattacharjee, ML Hill, H Wu, PS Chandakkar, JR Smith, MN Wegman IBM Journal of Research and Development 61 (4/5), 4: 1-4: 8, 2017 | 7 | 2017 |
| MIRank-KNN: multiple-instance retrieval of clinically relevant diabetic retinopathy images PS Chandakkar, R Venkatesan, B Li Journal of Medical Imaging 4 (3), 034003-034003, 2017 | 6 | 2017 |
| Improving vision-based self-positioning in intelligent transportation systems via integrated lane and vehicle detection PS Chandakkar, Y Wang, B Li 2015 IEEE Winter Conference on Applications of Computer Vision, 404-411, 2015 | 6 | 2015 |
| Joint Regression and Ranking for Image Enhancement PS Chandakkar, B Li IEEE Winter Conference on Applications of Computer Vision (WACV), 235-243, 2017 | 4 | 2017 |
| A structured approach to predicting image enhancement parameters PS Chandakkar, B Li 2016 IEEE Winter Conference on Applications of Computer Vision (WACV), 1-9, 2016 | 4 | 2016 |
| Investigating human factors in image forgery detection PS Chandakkar, B Li Proceedings of the 1st ACM International Workshop on Human Centered Event …, 2014 | 4 | 2014 |
| Relative learning from web images for content-adaptive enhancement PS Chandakkar, Q Tian, B Li 2015 IEEE International Conference on Multimedia and Expo (ICME), 1-6, 2015 | 3 | 2015 |
| A machine-learning approach to retrieving diabetic retinopathy images PS Chandakkar, R Venkatesan, B Li, HK Li Proceedings of the ACM Conference on Bioinformatics, Computational Biology …, 2012 | 3 | 2012 |
| Training optimization for neural networks with batch norm layers B Bhattacharjee, P Chandakkar, JR Smith US Patent App. 16/270,697, 2020 | 2 | 2020 |
| Systems and methods for a content-adaptive photo-enhancement recommender B Li, PS Chandakkar, Q Tian US Patent 9,576,343, 2017 | 1 | 2017 |
| Capturing Localized Image Artifacts through a CNN-based Hyper-image Representation PS Chandakkar, B Li arXiv preprint arXiv:1711.04945, 2017 | | 2017 |
| Towards Learning Representations in Visual Computing Tasks PS Chandakkar Arizona State University, 2017 | | 2017 |
| Video-Based Self-positioning for Intelligent Transportation Systems Applications PS Chandakkar, R Venkatesan, B Li Advances in Visual Computing, 718-729, 2014 | | 2014 |
Baoxin LiArizona State UniversityVerified email at asu.edu
