Convolutional neural network for hyperspectral image classification
Date of Issue2016
School of Electrical and Electronic Engineering
Hyperspectral Image Classification is an important research problem in remote sensing.Classification is one of the most popular topic in hyperspectral remote sensing. In the last twenty years, a huge quantity of methods were proposed to deal with the hyperspectral data classification problem. Deep learning has been shown to be very promissing for this problem. However, existing deep learning methods only try to learn features from a pixel/region independently without considering the dependency between different pixels/regions.This project will employ Convolutional Neural Networks for learning features based on the spatial-spectral information of hyperspectral images. Experiments are conducted on benchmark datasets.
DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing