Heuristic Compression Method for CNN Model Applying Quantization to a Combination of Structured and Unstructured Pruning Techniques

Model Compression is an actively pursued research field in recent years with the goal of deploying state-of-the-art deep neural networks. It is targeted to implementations which are based on power constrained and resource limited devices as the reduced model achieves without significant accuracy los...

詳細記述

書誌詳細

出版年:	IEEE Access
主要な著者:	Danhe Tian, Shinichi Yamagiwa, Koichi Wada
フォーマット:	論文
言語:	英語
出版事項:	IEEE 2024-01-01
主題:	Convolutional neural network model compression quantization structured pruning unstructured pruning
オンライン･アクセス:	https://ieeexplore.ieee.org/document/10528266/