Title
Three Dimensional Convolutional Neural Network Pruning with Regularization-Based Method.
Abstract
In recent years, three-dimensional convolutional neural network (3D CNN) is intensively applied in video analysis and receives good performance. However, 3D CNN leads to massive computation and storage consumption, which hinders its deployment on mobile and embedded devices. In this paper, we propose a three-dimensional regularization-based pruning method to assign different regularization parameters to different weight groups based on their importance to the network. Experiments show that the proposed method outperforms other popular methods in this area.
Year
DOI
Venue
2018
10.1109/icip.2019.8803541
international conference on image processing
Field
DocType
Volume
Convolutional neural network,Algorithm,Regularization (mathematics),Redundancy (engineering),Acceleration,Artificial intelligence,Artificial neural network,Machine learning,Mathematics,Computation,Pruning,Speedup
Journal
abs/1811.07555
ISSN
Citations 
PageRank 
ICIP 2019
2
0.36
References 
Authors
0
4
Name
Order
Citations
PageRank
Yuxin Zhang121.72
Huan Wang2199.48
Yang Luo3166.45
Roland Hu413417.51