ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2003.06757
  4. Cited By
Channel Pruning Guided by Classification Loss and Feature Importance

Channel Pruning Guided by Classification Loss and Feature Importance

15 March 2020
Jinyang Guo
Wanli Ouyang
Dong Xu
ArXivPDFHTML

Papers citing "Channel Pruning Guided by Classification Loss and Feature Importance"

5 / 5 papers shown
Title
Differentiable Channel Selection in Self-Attention For Person Re-Identification
Differentiable Channel Selection in Self-Attention For Person Re-Identification
Yancheng Wang
Nebojsa Jojic
Yingzhen Yang
29
0
0
13 May 2025
BiBench: Benchmarking and Analyzing Network Binarization
BiBench: Benchmarking and Analyzing Network Binarization
Haotong Qin
Mingyuan Zhang
Yifu Ding
Aoyu Li
Zhongang Cai
Ziwei Liu
F. I. F. Richard Yu
Xianglong Liu
MQ
AAML
34
36
0
26 Jan 2023
Unsupervised Learning of Accurate Siamese Tracking
Unsupervised Learning of Accurate Siamese Tracking
Qiuhong Shen
Leixian Qiao
Jinyang Guo
Peixia Li
Xin Li
Bo-wen Li
Weitao Feng
Weihao Gan
Wei Wu
Wanli Ouyang
32
41
0
04 Apr 2022
Prioritized Subnet Sampling for Resource-Adaptive Supernet Training
Prioritized Subnet Sampling for Resource-Adaptive Supernet Training
Bohong Chen
Mingbao Lin
Rongrong Ji
Liujuan Cao
26
2
0
12 Sep 2021
Carrying out CNN Channel Pruning in a White Box
Carrying out CNN Channel Pruning in a White Box
Yuxin Zhang
Mingbao Lin
Chia-Wen Lin
Jie Chen
Feiyue Huang
Yongjian Wu
Yonghong Tian
Rongrong Ji
VLM
39
58
0
24 Apr 2021
1