Class-Aware Self-Distillation for Remote Sensing Image Scene Classification-Reference-Cited by-同舟云学术

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Class-Aware Self-Distillation for Remote Sensing Image Scene Classification

Published:2024 Issue: Volume:17 Page:2173-2188
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:

Wu Bin¹^ORCID,Hao Siyuan²^ORCID,Wang Wei³^ORCID

Affiliation:

1. College of Information and Control Engineering, Qingdao University of Technology, Qingdao, China

2. School of Software Engineering, Beijing Jiaotong University, Beijing, China

3. Institute of Information Science, Beijing Jiaotong University, Beijing, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

http://xplorestaging.ieee.org/ielx7/4609443/10330207/10361538.pdf?arnumber=10361538

Reference67 articles.

1. Automatic landslide detection from remote-sensing imagery using a scene classification method based on BoVW and pLSA

2. Segment Optimization and Data-Driven Thresholding for Knowledge-Based Landslide Detection by Object-Based Image Analysis

3. Learning Rotation-Invariant Convolutional Neural Networks for Object Detection in VHR Optical Remote Sensing Images

4. Modeling and Detection of Geospatial Objects Using Texture Motifs

5. Semantic Annotation of High-Resolution Satellite Images via Weakly Supervised Learning

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