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-7: Machine Learning for Image Processing

Session Type: Poster
Time: Wednesday, 9 June, 13:00 - 13:45
Location: Gather.Town
Session Chair: C.-C. Jay Kuo, University of Southern California
 
IVMSP-7.1: SUPER-RESOLUTION AND INFECTION EDGE DETECTION CO-GUIDED LEARNING FOR COVID-19 CT SEGMENTATION
         Yu Sang; Liaoning Technical University
         Jinguang Sun; Liaoning Technical University
         Simiao Wang; Liaoning Technical University
         Heng Qi; Dalian University of Technology
         Keqiu Li; Tianjin University
 
IVMSP-7.2: GATING FEATURE DENSE NETWORK FOR SINGLE ANISOTROPIC MR IMAGE SUPER-RESOLUTION
         Weidong He; Chongqing University
         Yangjinan Hu; Columbia University
         Lulu Wang; Chongqing University
         Zhongshi He; Chongqing University
         Jinglong Du; Chongqing Medical University
 
IVMSP-7.3: ADAPTABLE ENSEMBLE DISTILLATION
         Yankai Wang; Fudan University
         Dawei Yang; Fudan University
         Wei Zhang; Fudan University
         Zhe Jiang; ARM Ltd.
         Wenqiang Zhang; Fudan University
 
IVMSP-7.4: A SCALE INVARIANT MEASURE OF FLATNESS FOR DEEP NETWORK MINIMA
         Akshay Rangamani; Massachusetts Institute of Technology
         Nam Nguyen; IBM Research
         Abhishek Kumar; Google Brain
         Dzung Phan; IBM Research
         Sang Chin; Boston University
         Trac D. Tran; Johns Hopkins University
 
IVMSP-7.5: MULTI-ORDER ADVERSARIAL REPRESENTATION LEARNING FOR COMPOSED QUERY IMAGE RETRIEVAL
         Zhixiao Fu; Zhejiang University
         Xinyuan Chen; East China Normal University
         Jianfeng Dong; Zhejiang Gongshang University
         Shouling Ji; Zhejiang University
 
IVMSP-7.6: DEEP NEURAL NETWORKS WITH FLEXIBLE COMPLEXITY WHILE TRAINING BASED ON NEURAL ORDINARY DIFFERENTIAL EQUATIONS
         Zhengbo Luo; Waseda University
         Sei-ichiro Kamata; Waseda University
         Zitang Sun; Waseda University
         Weilian Zhou; Waseda University