Integrating Coordinate Features in CNN-Based Remote Sensing Imagery Classification

The land cover classification has played an important role in remote sensing applications. However, most classification methods were designed based on the pixel features or local spatial features of the remote sensing image, which limits the classification accuracy and generalization. In order to fu...

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Veröffentlicht in:	IEEE geoscience and remote sensing letters 2022, Vol.19, p.1-5
Hauptverfasser:	Zhang, Fan, Yan, Minchao, Hu, Chen, Ni, Jun, Zhou, Yongsheng
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Chemical technology Classification Conditional random fields Convolution Convolutional neural network (CNN) deep neural network (NN) Feature extraction hyperspectral image (HSI) Hyperspectral imaging Image classification Imagery Information processing IP networks Kernel Land cover land cover classification Methods Neural networks Pixels polarimetric synthetic aperture radar (PolSAR) Radar imaging Random sampling Remote sensing SAR (radar) Spatial data Statistical sampling Synthetic aperture radar Training
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