A Novel Approach Combining Decoupling Training with Prototype-based Contrastive Learning for Tracking Long-Tailed Recording in Optical Aerial Imagery

Jianlin Xie*, Guanqun Wang, Tong Zhang, Shilong Fan, Yin Zhuang, He Chen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Scene classification is a classical task in optical aerial imagery. In practical applications, it is difficult to obtain a balanced training samples supporting model training. Therefore, the dataset usually follow the Long-Tailed distribution, which is challenge for classification task, especially for multi-categories scene classification. It would make model intend to learn the representation of head classes with majority samples, which lead to under-represent middle and tail classes with minority samples and affect a better classifier construction for long-tailed classification. In this article, a novel Prototypical Supervised Contrastive Learning Based on Decoupling Framework called PSCL-DF is proposed for Long-Tailed Classification in Optical Remote Sensing Imagery to make a better feature learning and better classifier leaning. Finally, extensive tests are performed on the two artificially generated long-tailed datasets, demonstrating the robustness and effectiveness of the proposed methods. Our results show that decoupling feature extraction and classification achieve significant performance gains.

Original languageEnglish
Title of host publicationIEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331515669
DOIs
Publication statusPublished - 2024
Event2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024 - Zhuhai, China
Duration: 22 Nov 202424 Nov 2024

Publication series

NameIEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024

Conference

Conference2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024
Country/TerritoryChina
CityZhuhai
Period22/11/2424/11/24

Keywords

  • aerial imagery scene classification
  • decouple training
  • Long tail

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