ASPS-4.3
EVOLUTIONARY NEURAL ARCHITECTURE DESIGN OF LIQUID STATE MACHINE FOR IMAGE CLASSIFICATION
Cheng Tang, University of Toyama, Japan; Junkai Ji, Qiuzhen Lin, Shenzhen University, China; Yan Zhou, Northeastern University, China
Session:
Integrative Signal Processing and Machine Learning for Multimodal Sensing and Processing
Track:
Applied Signal Processing Systems
Location:
Gather Area A
Presentation Time:
Wed, 11 May, 23:00 - 23:45 China Time (UTC +8)
Wed, 11 May, 15:00 - 15:45 UTC
Wed, 11 May, 15:00 - 15:45 UTC
Session Chair:
Li Liu, Chinese University of Hong Kong (SZ)
Session ASPS-4
ASPS-4.1: FAST FAULT DIAGNOSIS METHOD OF ROLLING BEARINGS IN MULTI-SENSOR MEASUREMENT ENVIROMENT
Zuozhou Pan, Zong Meng, Yanshan University, China; Zhiping Lin, Yuanjin Zheng, Nanyang Technological University, Singapore
ASPS-4.2: DETECTING ANOMALY IN CHEMICAL SENSORS VIA REGULARIZED CONTRASTIVE LEARNING
Diaa Badawi, Ahmet Enis Cetin, University of Illinois at Chicago, United States of America; Ishaan Bassi, Sule Ozev, Arizona State University, United States of America
ASPS-4.3: EVOLUTIONARY NEURAL ARCHITECTURE DESIGN OF LIQUID STATE MACHINE FOR IMAGE CLASSIFICATION
Cheng Tang, University of Toyama, Japan; Junkai Ji, Qiuzhen Lin, Shenzhen University, China; Yan Zhou, Northeastern University, China
ASPS-4.4: INVISIBLE AND EFFICIENT BACKDOOR ATTACKS FOR COMPRESSED DEEP NEURAL NETWORKS
Huy Phan, Yi Xie, Yingying Chen, Bo Yuan, Rutgers University, United States of America; Jian Liu, University of Tennessee, United States of America
ASPS-4.5: TENSOR-BASED ORTHOGONAL MATCHING PURSUIT WITH PHASE ROTATION FOR CHANNEL ESTIMATION IN HYBRID BEAMFORMING MIMO-OFDM SYSTEMS
Cheng-Hung Lo, Pei-Yun Tsai, National Central University, Taiwan