Hybrid CNN Bi-LSTM neural network for Hyperspectral image classification

arXiv:2402.10026v1 Announce Type: cross
Abstract: Hyper spectral images have drawn the attention of the researchers for its complexity to classify. It has nonlinear relation between the materials and the spectral information provided by the HSI image. Deep learning methods have shown superiority in learning this nonlinearity in comparison to traditional machine learning methods. Use of 3-D CNN along with 2-D CNN have shown great success for learning spatial and spectral features. However, it uses comparatively large number of parameters. Moreover, …

abstract arxiv attention bi-lstm classification cnn comparison complexity cs.cv deep learning eess.iv hybrid image images information lstm machine materials network neural network researchers type