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UPANets: Learning from the Universal Pixel Attention Neworks
Ching Hsun Tseng
,
Shin Jye Lee
*
, Jianan Feng
, Shengzhong Mao
, Yu Ping Wu
, Jia Yu Shang
, Xiao Jun Zeng
*
Corresponding author for this work
Institute of Management of Technology
Research output
:
Contribution to journal
›
Article
›
peer-review
6
Scopus citations
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Keyphrases
Attention Network
100%
CIFAR-10
25%
Computer Vision
50%
Convolutional Layer
75%
Customer Focus
25%
Deep Convolutional Neural Network (deep CNN)
25%
Deep Structure
25%
Efficient Convolutional Neural Network
25%
Global Information
25%
Network Applications
25%
Networked Learning
100%
Performance Improvement
25%
Pixel Attention
100%
Receptive Field
25%
Shared Parameters
25%
Successful Development
25%
Transformer
25%
Vision Building
25%
Computer Science
Attention (Machine Learning)
100%
Computer Hardware
33%
Computer Vision
66%
Convolutional Layer
100%
Convolutional Neural Network
33%
Deep Convolutional Neural Networks
33%
Global Information
33%
Graphics Processing Unit
66%
Receptive Field
33%
Successful Development
33%
Engineering
Computervision
66%
Convolutional Layer
100%
Convolutional Neural Network
66%
Graphics Processing Unit
66%
Receptive Field
33%
Earth and Planetary Sciences
Computer Vision
100%
Stacking
100%