Pol-NAS: A Neural Architecture Search Method With Feature Selection for PolSAR Image Classification-Reference-Cited by-同舟云学术

Pol-NAS: A Neural Architecture Search Method With Feature Selection for PolSAR Image Classification

Published:2022 Issue: Volume:15 Page:9339-9354
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Liu Guangyuan¹^ORCID,Li Yangyang¹^ORCID,Chen Yanqiao²^ORCID,Shang Ronghua¹^ORCID,Jiao Licheng¹^ORCID

Affiliation:

1. Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, International Research Center for Intelligent Perception and Computation, Joint International Research Laboratory of Intelligent Perception and Computation, Collaborative Innovation Center of Quantum Information of Shaanxi Province, School of Artificial Intelligence, Xidian University, Xi'an, China

2. 54th Research Institute of China Electronics Technology Group Corporation, Shijiazhuang, China

Funder

National Natural Science Foundation of China

Key Research and Development Program in Shaanxi Province of China

Higher Education Discipline Innovation Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

http://xplorestaging.ieee.org/ielx7/4609443/9656571/09928571.pdf?arnumber=9928571

Reference47 articles.

1. Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation

2. Progressive DARTS: Bridging the Optimization Gap for NAS in the Wild

3. Regularized Evolution for Image Classifier Architecture Search

4. Large-scale evolution of image classifiers;real;Proc Int Conf Mach Learn,0

5. Neural architecture search with reinforcement learning;zoph;Proc Int Conf Learn Representations,0

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