Parag S. Chandakkar
Parag S. Chandakkar
Graduate student, Arizona State University
Verified email at asu.edu - Homepage
Title
Cited by
Cited by
Year
Classification of Diabetic Retinopathy Images Using Multi-Class Multiple-Instance Learning Based on Color Correlogram Features
R Venkatesan, P Chandakkar, B Li, HK Li
39*
Strategies for Re-Training a Pruned Neural Network in an Edge Computing Paradigm
PS Chandakkar, Y Li, PLK Ding, B Li
Edge Computing (EDGE), 2017 IEEE International Conference on, 244-247, 2017
202017
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
142015
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, 86700Q, 2013
112013
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
72013
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
62015
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
42017
Joint Regression and Ranking for Image Enhancement
PS Chandakkar, B Li
IEEE Winter Conference on Applications of Computer Vision (WACV), 235-243, 2017
32017
MIRank-KNN: multiple-instance retrieval of clinically relevant diabetic retinopathy images
PS Chandakkar, R Venkatesan, B Li
Journal of Medical Imaging 4 (3), 034003, 2017
22017
A computational approach to relative aesthetics.
V Gattupalli, PS Chandakkar, B Li
ICPR, 2446-2451, 2016
2*2016
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
22016
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
22015
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
22012
Investigating Human Factors in Image Forgery Detection
PS Chandakkar, B Li
Proceedings of the 1st ACM International Workshop on Human Centered Event …, 2014
12014
Video-Based Self-positioning for Intelligent Transportation Systems Applications
PS Chandakkar, R Venkatesan, B Li
Advances in Visual Computing, 718-729, 2014
12014
Feature Extraction and Learning for Visual Data
B Li, R Venkatesan, PS Chandakkar
Feature Engineering for Machine Learning and Data Analytics, 55-85, 2018
2018
Capturing Localized Image Artifacts through a CNN-based Hyper-image Representation
PS Chandakkar, B Li
arXiv preprint arXiv:1711.04945, 2017
2017
Systems and methods for a content-adaptive photo-enhancement recommender
B Li, PS Chandakkar, Q Tian
US Patent 9,576,343, 2017
2017
Towards Learning Representations in Visual Computing Tasks
PS Chandakkar
Arizona State University, 2017
2017
Clinically Relevant Classification and Retrieval of Diabetic Retinopathy Images
PS Chandakkar
ARIZONA STATE UNIVERSITY, 2012
2012
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Articles 1–20