345 citations · 659 across the 21 of their papers we have counts for
5 papers · 1 filter
Learning Sparse Neural Networks with Identity Layers
Mingjian Ni, Guangyao Chen, Xiawu Zheng +3
The sparsity of Deep Neural Networks is well investigated to maximize the performance and reduce the size of overparameterized networks as possible. Existing methods focus on pruni…
Population-Based Evolutionary Gaming for Unsupervised Person Re-identification
Yunpeng Zhai, Peixi Peng, Mengxi Jia +4
Unsupervised person re-identification has achieved great success through the self-improvement of individual neural networks. However, limited by the lack of diversity of discrimina…
Picking Up Quantization Steps for Compressed Image Classification
Li Ma, Peixi Peng, Guangyao Chen +3
The sensitivity of deep neural networks to compressed images hinders their usage in many real applications, which means classification networks may fail just after taking a screens…
Learning with Fantasy: Semantic-Aware Virtual Contrastive Constraint for Few-Shot Class-Incremental Learning
Zeyin Song, Yifan Zhao, Yujun Shi +3
Few-shot class-incremental learning (FSCIL) aims at learning to classify new classes continually from limited samples without forgetting the old classes. The mainstream framework t…
Training Full Spike Neural Networks via Auxiliary Accumulation Pathway
Guangyao Chen, Peixi Peng, Guoqi Li +1
Due to the binary spike signals making converting the traditional high-power multiply-accumulation (MAC) into a low-power accumulation (AC) available, the brain-inspired Spiking Ne…