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20152022
most citedImproving Neural Network Quantization without Retraining using Outlier Channel Splitting

151 citations · 389 across the 13 of their papers we have counts for

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cs.CV2022★ 13 cited

Structured Pruning is All You Need for Pruning CNNs at Initialization

Yaohui Cai, Weizhe Hua, Hongzheng Chen +3

Pruning is a popular technique for reducing the model size and computational cost of convolutional neural networks (CNNs). However, a slow retraining or fine-tuning procedure is of…

cs.CV2020

Optimizing JPEG Quantization for Classification Networks

Zhijing Li, Christopher De Sa, Adrian Sampson

Deep learning for computer vision depends on lossy image compression: it reduces the storage required for training and test data and lowers transfer costs in deployment. Mainstream…