3 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.CV2021
AIP: Adversarial Iterative Pruning Based on Knowledge Transfer for Convolutional Neural Networks
Jingfei Chang, Yang Lu, Ping Xue +2
With the increase of structure complexity, convolutional neural networks (CNNs) take a fair amount of computation cost. Meanwhile, existing research reveals the salient parameter r…
cs.CV2021★ 3 cited
ACP: Automatic Channel Pruning via Clustering and Swarm Intelligence Optimization for CNN
Jingfei Chang, Yang Lu, Ping Xue +2
As the convolutional neural network (CNN) gets deeper and wider in recent years, the requirements for the amount of data and hardware resources have gradually increased. Meanwhile,…
cs.CV2020★ 2 cited
UCP: Uniform Channel Pruning for Deep Convolutional Neural Networks Compression and Acceleration
Jingfei Chang, Yang Lu, Ping Xue +2
To apply deep CNNs to mobile terminals and portable devices, many scholars have recently worked on the compressing and accelerating deep convolutional neural networks. Based on thi…