FuSENet: fused squeeze‐and‐excitation network for spectral‐spatial hyperspectral image classification-Reference-Cited by-同舟云学术

FuSENet: fused squeeze‐and‐excitation network for spectral‐spatial hyperspectral image classification

Published:2020-05-15 Issue:8 Volume:14 Page:1653-1661
ISSN:1751-9667
Container-title:IET Image Processing
language:en
Short-container-title:IET Image Processing

Author:

Roy Swalpa Kumar¹^ORCID,Dubey Shiv Ram²,Chatterjee Subhrasankar³,Baran Chaudhuri Bidyut⁴

Affiliation:

1. Department of Computer Science & EngineeringJalpaiguri Government of Engineering CollegeWest Bengal735102India

2. Computer Vision GroupIndian Institute of Information TechnologySri City, ChittoorAndhra Pradesh517646India

3. Department of Computer Science & EngineeringIndian Institute of TechnologyKharagpurWest Bengal721302India

4. Computer Vision and Pattern Recognition UnitIndian Statistical InstituteKolkata700108India

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2019.1462

Reference45 articles.

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2. ImageNet Large Scale Visual Recognition Challenge

3. Deep Residual Learning for Image Recognition

4. 2018 Proc. IEEE Conf. on Computer Vision and Pattern Recognition J. Hu L. Shen G. Sun Squeeze‐and‐excitation networks 7132 7141

5. 2014 Proc. IEEE Conf. on Computer Vision and Pattern Recognition R. Girshick J. Donahue T. Darrell Rich feature hierarchies for accurate object detection and semantic segmentation 580 587

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