Weakly Correlated Distillation for Remote Sensing Object Recognition-Reference-Cited by-同舟云学术

Weakly Correlated Distillation for Remote Sensing Object Recognition

Published:2023 Issue: Volume:61 Page:1-11
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Zhao Wenda¹^ORCID,Lv Xiangzhu¹,Wang Haipeng²^ORCID,Liu Yu³^ORCID,He You³^ORCID,Lu Huchuan¹^ORCID

Affiliation:

1. Key Laboratory of Intelligent Control and Optimization for Industrial Equipment, Ministry of Education, and the School of Information and Communication Engineering, Dalian University of Technology, Dalian, China

2. Research Institute of Information Fusion, Naval Aviation University, Yantai, China

3. Department of Electronic Engineering, Tsinghua University, Beijing, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10255741.pdf?arnumber=10255741

Reference55 articles.

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

2. Hierarchical and Robust Convolutional Neural Network for Very High-Resolution Remote Sensing Object Detection

3. Meta-Learning With Differentiable Convex Optimization

4. Prototypical Siamese Networks for Few-shot Learning

5. Fine-Grained Visual Classification via Progressive Multi-granularity Training of Jigsaw Patches

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