11 citations · 12 across the 2 of their papers we have counts for
5 papers
Task-Adaptive Incremental Learning for Intelligent Edge Devices
Zhuwei Qin, Fuxun Yu, Xiang Chen
Convolutional Neural Networks (CNNs) are used for a wide range of image-related tasks such as image classification and object detection. However, a large pre-trained CNN model cont…
Interpreting and Evaluating Neural Network Robustness
Fuxun Yu, Zhuwei Qin, Chenchen Liu +3
Recently, adversarial deception becomes one of the most considerable threats to deep neural networks. However, compared to extensive research in new designs of various adversarial…
Distilling Critical Paths in Convolutional Neural Networks
Fuxun Yu, Zhuwei Qin, Xiang Chen
Neural network compression and acceleration are widely demanded currently due to the resource constraints on most deployment targets. In this paper, through analyzing the filter ac…
Demystifying Neural Network Filter Pruning
Zhuwei Qin, Fuxun Yu, ChenChen Liu +1
Based on filter magnitude ranking (e.g. L1 norm), conventional filter pruning methods for Convolutional Neural Networks (CNNs) have been proved with great effectiveness in computat…
Functionality-Oriented Convolutional Filter Pruning
Zhuwei Qin, Fuxun Yu, Chenchen Liu +1
The sophisticated structure of Convolutional Neural Network (CNN) allows for outstanding performance, but at the cost of intensive computation. As significant redundancies inevitab…