ARS-09: Explainable Machine Learning for Computer Vision |
Interactive Q&A Time: Tuesday, 27 October, 14:30 - 14:55 |
Virtual Session: View on Virtual Platform |
Session Chair: Gene Cheung, York University |
ARS-09.1: HRINET: ALTERNATIVE SUPERVISION NETWORK FOR HIGH-RESOLUTION CT IMAGE INTERPOLATION |
Jiawei Li; University of Ottawa |
Jae Chul Koh; the Korea University Anam Hospital |
Won-Sook Lee; University of Ottawa |
ARS-09.2: INTERPRETABLE SYNTHETIC REDUCED NEAREST NEIGHBOR: AN EXPECTATION MAXIMIZATION APPROACH |
Pooya Tavallali; University of California, Merced |
Peyman Tavallali; Independet Researcher |
Mohammad Reza Khosravi; Shiraz University of Technology |
Mukesh Singhal; University of California, Merced |
ARS-09.3: AIM-NET: BRING IMPLICIT EULER TO NETWORK DESIGN |
Qiongwen Yuan; Wuhan University |
Jingwei He; Wuhan University |
Lei Yu; Wuhan University |
Gang Zheng; INRIA Lille |
ARS-09.4: MULTI-SCALE EXPLAINABLE FEATURE LEARNING FOR PATHOLOGICAL IMAGE ANALYSIS USING CONVOLUTIONAL NEURAL NETWORKS |
Kazuki Uehara; National Institute of Advanced Industrial Science and Technology (AIST) |
Masahiro Murakawa; National Institute of Advanced Industrial Science and Technology (AIST) |
Hirokazu Nosato; National Institute of Advanced Industrial Science and Technology (AIST) |
Hidenori Sakanashi; National Institute of Advanced Industrial Science and Technology (AIST) |
ARS-09.5: SALIENCY-DRIVEN CLASS IMPRESSIONS FOR FEATURE VISUALIZATION OF DEEP NEURAL NETWORKS |
Sravanti Addepalli; Indian Institute of Science |
Dipesh Tamboli; Indian Institute of Technology Bombay |
Venkatesh Babu Radhakrishnan; Indian Institute of Science |
Biplab Banerjee; Indian Institute of Technology Bombay |
ARS-09.6: VARIATIONAL ENCODER-BASED RELIABLE CLASSIFICATION |
Chitresh Bhushan; GE Research |
Zhaoyuan Yang; GE Research |
Nurali Virani; GE Research |
Naresh Iyer; GE Research |
ARS-09.7: HOUGHENCODER: NEURAL NETWORK ARCHITECTURE FOR DOCUMENT IMAGE SEMANTIC SEGMENTATION |
Alexander Sheshkus; Smart Engines Service LLC |
Dmitry Nikolaev; Institute for Information Transmission Problems (Kharkevich Institute) Russian Academy of Sciences |
Vladimir L Arlazarov; Federal Research Center “Computer Science and Control” of Russian Academy of Sciences |