2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

Technical Program

IVMSP-10: Metric Learning and Interpretability

Session Type: Poster
Time: Wednesday, 9 June, 13:00 - 13:45
Location: Gather.Town
Session Chair: Shashikant Patil, SVKMs NMIMS Shirpur
 
IVMSP-10.1: DEEP SEMI-SUPERVISED METRIC LEARNING VIA IDENTIFICATION OF MANIFOLD MEMBERSHIPS
         Furen Zhuang; University of Illinois at Urbana-Champaign
         Pierre Moulin; University of Illinois at Urbana-Champaign
 
IVMSP-10.2: A RANKED SIMILARITY LOSS FUNCTION WITH PAIR WEIGHTING FOR DEEP METRIC LEARNING
         Jian Wang; Shanghai Ocean University
         Zhichao Zhang; Shanghai Ocean University
         Dongmei Huang; Shanghai University of Electric Power
         Wei Song; Shanghai Ocean University
         Quanmiao Wei; Donghai Bureau of the Ministry of Natural Resources
         Xinyue Li; Shanghai Ocean University
 
IVMSP-10.3: STATISTICAL DISTANCE METRIC LEARNING FOR IMAGE SET RETRIEVAL
         Ting-Yao Hu; Carnegie Mellon University
         Alexander G Hauptmann; Carnegie Mellon University
 
IVMSP-10.4: DISTRIBUTION-AWARE HIERARCHICAL WEIGHTING METHOD FOR DEEP METRIC LEARNING
         Yinong Zhu; Chongqing University
         Yong Feng; Chongqing University
         Mingliang Zhou; University of Macau
         Baohua Qiang; Guilin University of Electronic Technology
         Leong Hou U; University of Macau
         Jiajie Zhu; Chongqing University
 
IVMSP-10.5: INTEGRATED GRAD-CAM: SENSITIVITY-AWARE VISUAL EXPLANATION OF DEEP CONVOLUTIONAL NETWORKS VIA INTEGRATED GRADIENT-BASED SCORING
         Sam Sattarzadeh; University of Toronto
         Mahesh Sudhakar; University of Toronto
         Konstantinos N. Plataniotis; University of Toronto
         Jongseong Jang; LG AI Research
         Yeonjeong Jeong; LG AI Research
         Hyunwoo Kim; LG AI Research
 
IVMSP-10.6: VISUALIZING ASSOCIATION IN EXEMPLAR-BASED CLASSIFICATION
         Taiga Kashima; University of Tokyo
         Ryuichiro Hataya; University of Tokyo
         Hideki Nakayama; University of Tokyo