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Status: Unchecked ×Keyword: convolutional neural network pruning ×Clear all

2 claims from 2 papers

1. Computer Science › Advanced Neural Network Applications

   Convolutional Neural Network Pruning with Structural Redundancy Reduction

   Wang, Li and Wang · arXiv (Cornell University) · 2021

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   1. Unchecked“We first statistically model the network pruning problem in a redundancy reduction perspective and find that pruning in the layer(s) with the most structural redundancy outperforms pruning the least important filters across all layers.”

2. Computer Science › Advanced Neural Network Applications

   Towards compressed and efficient CNN architectures via pruning

   Narkhede, Mahajan, Bartakke and Sutaone · Discover Computing · 2024

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   1. Unchecked“For Intel image, CIFAR10 and CIFAR100 datasets the proposed pruning method has compressed AlexNet by 83.2%, 87.19%, and 79.7%, VGG-16 by 83.7%, 85.11%, and 84.06% and ResNet-50 by 62.99%, 62.3% and 58.34% respectively.”