17 citations · 63 across the 15 of their papers we have counts for
7 papers · 1 filter
Cyclic Learning: Bridging Image-level Labels and Nuclei Instance Segmentation
Yang Zhou, Yongjian Wu, Zihua Wang +5
Nuclei instance segmentation on histopathology images is of great clinical value for disease analysis. Generally, fully-supervised algorithms for this task require pixel-wise manua…
Data and Knowledge Co-driving for Cancer Subtype Classification on Multi-Scale Histopathological Slides
Bo Yu, Hechang Chen, Yunke Zhang +5
Artificial intelligence-enabled histopathological data analysis has become a valuable assistant to the pathologist. However, existing models lack representation and inference abili…
Convolutional Neural Network Pruning with Structural Redundancy Reduction
Zi Wang, Chengcheng Li, Xiangyang Wang
Convolutional neural network (CNN) pruning has become one of the most successful network compression approaches in recent years. Existing works on network pruning usually focus on…
Investigating Channel Pruning through Structural Redundancy Reduction -- A Statistical Study
Chengcheng Li, Zi Wang, Dali Wang +2
Most existing channel pruning methods formulate the pruning task from a perspective of inefficiency reduction which iteratively rank and remove the least important filters, or find…
Speeding up convolutional networks pruning with coarse ranking
Zi Wang, Chengcheng Li, Dali Wang +2
Channel-based pruning has achieved significant successes in accelerating deep convolutional neural network, whose pipeline is an iterative three-step procedure: ranking, pruning an…
Single-shot Channel Pruning Based on Alternating Direction Method of Multipliers
Chengcheng Li, Zi Wang, Xiangyang Wang +1
Channel pruning has been identified as an effective approach to constructing efficient network structures. Its typical pipeline requires iterative pruning and fine-tuning. In this…