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Parag S. Chandakkar
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2010 – 2019
- 2017
- [b1]Parag Shridhar Chandakkar:
Towards Learning Representations in Visual Computing Tasks. Arizona State University, Tempe, USA, 2017 - [c13]Parag S. Chandakkar, Yikang Li, Pak Lun Kevin Ding, Baoxin Li:
Strategies for Re-Training a Pruned Neural Network in an Edge Computing Paradigm. EDGE 2017: 244-247 - [c12]Parag Shridhar Chandakkar, Baoxin Li:
Joint Regression and Ranking for Image Enhancement. WACV 2017: 235-243 - [i9]Parag S. Chandakkar, Baoxin Li:
Joint Regression and Ranking for Image Enhancement. CoRR abs/1704.01235 (2017) - [i8]Parag S. Chandakkar, Vijetha Gattupalli, Baoxin Li:
A Computational Approach to Relative Aesthetics. CoRR abs/1704.01248 (2017) - [i7]Parag S. Chandakkar, Baoxin Li:
A Structured Approach to Predicting Image Enhancement Parameters. CoRR abs/1704.01249 (2017) - [i6]Parag S. Chandakkar, Qiongjie Tian, Baoxin Li:
Relative Learning from Web Images for Content-adaptive Enhancement. CoRR abs/1704.01250 (2017) - [i5]Parag S. Chandakkar, Yilin Wang, Baoxin Li:
Improving Vision-based Self-positioning in Intelligent Transportation Systems via Integrated Lane and Vehicle Detection. CoRR abs/1704.01256 (2017) - [i4]Parag S. Chandakkar, Baoxin Li:
Investigating Human Factors in Image Forgery Detection. CoRR abs/1704.01262 (2017) - [i3]Ragav Venkatesan, Parag S. Chandakkar, Baoxin Li:
Classification of Diabetic Retinopathy Images Using Multi-Class Multiple-Instance Learning Based on Color Correlogram Features. CoRR abs/1704.01264 (2017) - [i2]Devi Archana Paladugu, Parag S. Chandakkar, Peng Zhang, Baoxin Li:
Supporting Navigation of Outdoor Shopping Complexes for Visually-impaired Users through Multi-modal Data Fusion. CoRR abs/1704.01266 (2017) - [i1]Parag Shridhar Chandakkar, Baoxin Li:
Capturing Localized Image Artifacts through a CNN-based Hyper-image Representation. CoRR abs/1711.04945 (2017) - 2016
- [c11]Vijetha Gattupalli, Parag S. Chandakkar, Baoxin Li:
A computational approach to relative aesthetics. ICPR 2016: 2446-2451 - [c10]Parag Shridhar Chandakkar, Baoxin Li:
A structured approach to predicting image enhancement parameters. WACV 2016: 1-9 - 2015
- [c9]Ragav Venkatesan, Parag Shridhar Chandakkar, Baoxin Li:
Simpler Non-Parametric Methods Provide as Good or Better Results to Multiple-Instance Learning. ICCV 2015: 2605-2613 - [c8]Parag Shridhar Chandakkar, Qiongjie Tian, Baoxin Li:
Relative learning from web images for content-adaptive enhancement. ICME 2015: 1-6 - [c7]Parag S. Chandakkar, Yilin Wang, Baoxin Li:
Improving Vision-Based Self-Positioning in Intelligent Transportation Systems via Integrated Lane and Vehicle Detection. WACV 2015: 404-411 - 2014
- [c6]Parag S. Chandakkar, Ragav Venkatesan, Baoxin Li:
Video-Based Self-positioning for Intelligent Transportation Systems Applications. ISVC (1) 2014: 718-729 - [c5]Parag Shridhar Chandakkar, Baoxin Li:
Investigating Human Factors in Image Forgery Detection. HuEvent@MM 2014: 41-44 - 2013
- [c4]Devi Archana Paladugu, Parag S. Chandakkar, Peng Zhang, Baoxin Li:
Supporting navigation of outdoor shopping complexes for visuallyimpaired users through multi-modal data fusion. ICME 2013: 1-7 - [c3]Parag S. Chandakkar, Ragav Venkatesan, Baoxin Li:
Retrieving clinically relevant diabetic retinopathy images using a multi-class multiple-instance framework. Computer-Aided Diagnosis 2013: 86700Q - 2012
- [c2]Parag S. Chandakkar, Ragav Venkatesan, Baoxin Li, Helen K. Li:
A machine-learning approach to retrieving diabetic retinopathy images. BCB 2012: 588-589 - [c1]Ragav Venkatesan, Parag S. Chandakkar, Baoxin Li, Helen K. Li:
Classification of diabetic retinopathy images using multi-class multiple-instance learning based on color correlogram features. EMBC 2012: 1462-1465
Coauthor Index
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