Multiscale Context-aware Ensemble Deep Learning for Efficient Hyperspectral Image Analysis

Multiscale Context-aware Ensemble Deep Learning for Efficient Hyperspectral Image Analysis is a novel approach for hyperspectral image analysis that combines multiscale contextual information with ensemble deep learning techniques. The proposed method achieves state-of-the-art accuracy while maintaining high efficiency. By leveraging the multiscale contextual information, the method can effectively handle the high-dimensional data and capture the spatial and spectral features of hyperspectral images. The ensemble deep learning techniques further enhance its performance by aggregating the predictions from multiple neural networks. Experimental results on benchmark datasets demonstrate the superiority of the proposed method over the state-of-the-art methods.