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Deep Learning for Hyperspectral Image Classification by nirmala periasamy is a document available to read on EtoBox.

This document discusses using convolutional neural networks (CNNs) for feature extraction and classification of hyperspectral images. It proposes a regularized deep feature extraction method using a CNN to extract nonlinear, discriminant, and invariant features from hyperspectral images. Furthermore, it addresses the issue of limited training samples by using strategies like L2 regularization and dropout to avoid overfitting. The document introduces a 3D CNN model with combined regularization to extract eff

Author

nirmala periasamy

Language

EN