EPSANet: An Efficient Pyramid Squeeze Attention Block on Convolutional Neural Network
Shenzhen University · Chinese Academy of Medical Sciences & Peking Union Medical College · +3 more institutions
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Abstract
No abstract available for this paper.
Citation impact
304
total citations
- FWCI
- 111.36
- Percentile
- 100%
- References
- 34
Citations per year
Authors
5- HZHu Zhang
Shenzhen University, Chinese Academy of Medical Sciences & Peking Union Medical College, National Supercomputing Center in Shenzhen
- KZKeke Zu
Shenzhen University, Chinese Academy of Medical Sciences & Peking Union Medical College, National Supercomputing Center in Shenzhen
- JLJian LüCorresponding
Shenzhen University, Chinese Academy of Medical Sciences & Peking Union Medical College, National Supercomputing Center in Shenzhen
- YZYuru Zou
Shenzhen University, Chinese Academy of Medical Sciences & Peking Union Medical College, National Supercomputing Center in Shenzhen
- DMDeyu Meng
Macau University of Science and Technology, Xi'an Jiaotong University
Topics & keywords
Topics
Keywords
- Computer science
- Block (permutation group theory)
- Artificial intelligence
- Convolutional neural network
- Pyramid (geometry)
- Convolution (computer science)
- Pattern recognition (psychology)
- Object detection
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