Class-Incremental Novel Category Discovery in Remote Sensing Image Scene Classification via Contrastive Learning-Reference-Cited by-同舟云学术

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Class-Incremental Novel Category Discovery in Remote Sensing Image Scene Classification via Contrastive Learning

Published:2024 Issue: Volume:17 Page:9214-9225
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:

Zhou Yifan¹^ORCID,Zhu Haoran¹^ORCID,Xu Chang¹^ORCID,Zhang Ruixiang¹^ORCID,Hua Guang²^ORCID,Yang Wen¹^ORCID

Affiliation:

1. School of Electronic Information, Wuhan University, Wuhan, China

2. Infocomm Technology Cluster, Singapore Institute of Technology, Singapore

Funder

National Natural Science Foundation of China

Regional Innovation and Development Joint

NSFC general program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/4609443/10330207/10505729.pdf?arnumber=10505729

Reference60 articles.

1. Remote Sensing Image Scene Classification Meets Deep Learning: Challenges, Methods, Benchmarks, and Opportunities

2. Domain Adaptation Network for Cross-Scene Classification

3. Branch Feature Fusion Convolution Network for Remote Sensing Scene Classification

4. Deep Object-Centric Pooling in Convolutional Neural Network for Remote Sensing Scene Classification

5. AutoNovel: Automatically Discovering and Learning Novel Visual Categories

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