Convolution Smooth: A Post-Training Quantization Method for Convolutional Neural Networks

Convolution Smooth: A Post-Training Quantization Method for Convolutional Neural Networks

Convolutional neural network (CNN) quantization is an efficient model compression technique primarily used for accelerating inference and optimizing resources. However, existing methods often apply different quantization strategies to activations and weights, without considering their interplay. To...

Full description

Saved in:
Bibliographic Details
Main Authors: Yongyuan Chen, Zhendao Wang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Convolutional neural network
post-training quantization
tensor scaling
factor fusion
Online Access:https://ieeexplore.ieee.org/document/10955493/
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://ieeexplore.ieee.org/document/10955493/

Similar Items