DF2Net: Differential Feature Fusion Network for Hyperspectral Image Classification

• Published in: IEEE journal of selected topics in applied earth observations and remote sensing Vol. 17; pp. 10660 - 10673
• Main Authors: Wang, Qingwang, Huang, Jiangbo, Meng, Yuanqin, Shen, Tao
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Advantageous feature differential enhancement fusion (AFDEF); Apexes; Artificial neural networks; Classification; Convolution; Convolutional neural networks; convolutional neural networks (CNNs); Correlation; Data mining; Feature extraction; hypergraph convolutional network; hyperspectral image (HSI) classification; Hyperspectral imaging; Image classification; Information retrieval; Neural networks; Training; Transformers

Recently, hybrid networks, combining graph convolutional networks (GCNs) and convolutional neural networks into a unified framework, have garnered significant attention in hyperspectral image (HSI) classification. However, existing hybrid networks have the following limitations. 1) Existing methods...