Hyperspectral Image Classification

40 papers with code • 6 benchmarks • 5 datasets

Hyperspectral image classification is the task of classifying a class label to every pixel in an image that was captured using (hyper)spectral sensors.

( Image credit: Shorten Spatial-spectral RNN with Parallel-GRU for Hyperspectral Image Classification )

Greatest papers with code

HSI-CNN: A Novel Convolution Neural Network for Hyperspectral Image

eecn/Hyperspectral-Classification 28 Feb 2018

In this paper, we propose a novel convolutional neural network framework for the characteristics of hyperspectral image data, called HSI-CNN.

General Classification Hyperspectral Image Classification

Going Deeper with Contextual CNN for Hyperspectral Image Classification

eecn/Hyperspectral-Classification 12 Apr 2016

The initial spatial and spectral feature maps obtained from the multi-scale filter bank are then combined together to form a joint spatio-spectral feature map.

General Classification Hyperspectral Image Classification

Deep Learning for Classification of Hyperspectral Data: A Comparative Review

nshaud/DeepHyperX IEEE Geoscience and Remote Sensing Magazine 2019

1 This article is intended for both data scientists with interest in hyperspectral data and remote sensing experts eager to apply deep learning techniques to their own dataset.

General Classification Hyperspectral Image Classification

Graph Convolutional Networks for Hyperspectral Image Classification

danfenghong/IEEE_TGRS_GCN 6 Aug 2020

Convolutional neural networks (CNNs) have been attracting increasing attention in hyperspectral (HS) image classification, owing to their ability to capture spatial-spectral feature representations.

General Classification Hyperspectral Image Classification

Feature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep (Overview and Toolbox)

BehnoodRasti/HyFTech-Hyperspectral-Shallow-Deep-Feature-Extraction-Toolbox 5 Mar 2020

The advances in feature extraction have been inspired by two fields of research, including the popularization of image and signal processing as well as machine (deep) learning, leading to two types of feature extraction approaches named shallow and deep techniques.

General Classification Hyperspectral Image Classification

Hyperspectral Image Classification with Markov Random Fields and a Convolutional Neural Network

xiangyongcao/CNN_HSIC_MRF 1 May 2017

This paper presents a new supervised classification algorithm for remotely sensed hyperspectral image (HSI) which integrates spectral and spatial information in a unified Bayesian framework.

General Classification Hyperspectral Image Classification