Composite Neighbor-Aware Convolutional Metric Networks for Hyperspectral Image Classification

Supervised classification of hyperspectral image (HSI) is generally required to obtain better performance in spectral-spatial feature learning by fully using complex pixel- and superpixel-level interdependencies with small labeled samples. Limited by the local regular convolutions, convolutional neu...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems 2024-07, Vol.35 (7), p.9297-9311
Hauptverfasser:	Liu, Qichao, Xiao, Liang, Huang, Nan, Tang, Jinhui
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial neural networks Classification Composite convolution (CoConv) composite neighbors Convolution Convolutional neural networks Deep learning Feature extraction Graphical representations hyperspectral image (HSI) classification Hyperspectral imaging Image classification Learning systems Machine learning Measurement mini-batch metric classifier Neural networks Pixels Spatial discrimination learning Task analysis
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