Filter Pruning Without Damaging Networks Capacity

Filter Pruning Without Damaging Networks Capacity

Due to its over-parameterized design, the deep convolutional neural networks lead to a huge amount of parameters and high computational cost, making it difficult to deploy on some devices with limited computational resources in reality. In this paper, we propose a method of filter pruning without da...

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Bibliographic Details
Main Authors: Yuding Zuo, Bo Chen, Te Shi, Mengfan Sun
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Convolutional neural networks
filter pruning
filter similarity
model capacity
networks compression and acceleration
Online Access:https://ieeexplore.ieee.org/document/9091183/

Internet

https://ieeexplore.ieee.org/document/9091183/

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