DeepLab-Based Spatial Feature Extraction for Hyperspectral Image Classification
DeepLab-Based Spatial Feature Extraction for Hyperspectral Image Classification is a scholarly work, published in 2019 in ''IEEE Geoscience and Remote Sensing Letters''. The main subjects of the publication include image, segmentation, artificial intelligence, feature extraction, image segmentation, computer science, remote sensing, support vector machine, feature, pixel, machine learning, pattern recognition, and hyperspectral imaging. Experimental results on two public HSI data sets demonstrate that the proposed framework outperformed the traditional methods and the existing deep learning-based methods, especially for small-scale classes.