Feature Consistency-Based Prototype Network for Open-Set Hyperspectral Image Classification

• Published in: IEEE transaction on neural networks and learning systems Vol. 35; no. 7; pp. 9286 - 9296
• Main Authors: Xie, Zhuojun, Duan, Puhong, Liu, Wang, Kang, Xudong, Wei, Xiaohui, Li, Shutao
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.07.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Classification; Classification algorithms; Clustering; Clustering methods; Contrastive clustering; Contrastive learning; Convolutional neural networks; feature consistency; Feature extraction; hyperspectral image (HSI); Hyperspectral imaging; Image classification; Modules; open-set classification; prototype network; Prototypes; Testing; Training

Hyperspectral image (HSI) classification methods have made great progress in recent years. However, most of these methods are rooted in the closed-set assumption that the class distribution in the training and testing stages is consistent, which cannot handle the unknown class in open-world scenes....