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Found 5 papers, 2 papers with code
EarthMapper: A Tool Box for the Semantic Segmentation of Remote Sensing Imagery
Deep learning continues to push state-of-the-art performance for the semantic segmentation of color (i. e., RGB) imagery; however, the lack of annotated data for many remote sensing sensors (i. e. hyperspectral imagery (HSI)) prevents researchers from taking advantage of this recent success.
Machine learning based hyperspectral image analysis: A survey
The paper is comprehensive in coverage of both hyperspectral image analysis tasks and machine learning algorithms.
A Tutorial on Modeling and Inference in Undirected Graphical Models for Hyperspectral Image Analysis
However, graphical models have not been easily accessible to the larger remote sensing community as they are not discussed in standard remote sensing textbooks and not included in the popular remote sensing software and toolboxes.
Multitask Learning of Vegetation Biochemistry from Hyperspectral Data
Statistical models have been successful in accurately estimating the biochemical contents of vegetation from the reflectance spectra.
Spectral Angle Based Unary Energy Functions for Spatial-Spectral Hyperspectral Classification using Markov Random Fields
We compare the proposed methods with the state-of-the-art Markov random field methods that use support vector machines and Gaussian processes with squared exponential kernel/covariance function.
