SS-12.5
Low Precision Local Learning for Hardware-friendly Neuromorphic Visual Recognition
Jyotibdha Acharya, Laxmi R Iyer, Wenyu Jiang, Institute of Infocomm Research, A*STAR, Singapore
Session:
Towards Neuromorphic Machine Intelligence: Spike-based Representation, Learning, and Signal Processing
Track:
Special Sessions
Location:
Gather Area A
Presentation Time:
Wed, 11 May, 22:00 - 22:45 China Time (UTC +8)
Wed, 11 May, 14:00 - 14:45 UTC
Wed, 11 May, 14:00 - 14:45 UTC
Session Co-Chairs:
Haizhou Li, The Chinese University of Hongkong and Jibin Wu, National University of Singapore and Malu Zhang, National University of Singapore
Session SS-12
SS-12.1: MOTIF-TOPOLOGY AND REWARD-LEARNING IMPROVED SPIKING NEURAL NETWORK FOR EFFICIENT MULTI-SENSORY INTEGRATION
Shuncheng Jia, Tielin Zhang, Hongxing Liu, Bo Xu, Institute of Automation, Chinese Academy of Sciences, China; Ruichen Zuo, School of Information and Electronics, Beijing Institute of Technology, China
SS-12.2: EVENT-BASED MULTIMODAL SPIKING NEURAL NETWORK WITH ATTENTION MECHANISM
Qianhui Liu, Dong Xing, Lang Feng, Huajin Tang, Gang Pan, Zhejiang University, China
SS-12.3: GRADUAL SURROGATE GRADIENT LEARNING IN DEEP SPIKING NEURAL NETWORKS
Yi Chen, Silin Zhang, Shiyu Ren, Hong Qu, University of Electronic Science and Technology of China, China
SS-12.4: AXONAL DELAY AS A SHORT-TERM MEMORY FOR FEED FORWARD DEEP SPIKING NEURAL NETWORKS
Pengfei Sun, Dick Botteldooren, Ghent University, Belgium; Longwei Zhu, Institute for Infocomm Research, A*STAR, Singapore
SS-12.5: Low Precision Local Learning for Hardware-friendly Neuromorphic Visual Recognition
Jyotibdha Acharya, Laxmi R Iyer, Wenyu Jiang, Institute of Infocomm Research, A*STAR, Singapore
SS-12.6: A HYBRID LEARNING FRAMEWORK FOR DEEP SPIKING NEURAL NETWORKS WITH ONE-SPIKE TEMPORAL CODING
Jiadong Wang, Jibin Wu, Malu Zhang, Qi Liu, Haizhou Li, National University of Singapore, Singapore