There are 3 repositories under hsi-classification topic.
Pytorch implementation of Multimodal Fusion Transformer for Remote Sensing Image Classification.
Pytorch and Keras Implementations of Hyperspectral Image Classification -- Traditional to Deep Models: A Survey for Future Prospects.
MCNN-CP:Hyperspectral Image Classification Using Mixed Convolutions and Covariance Pooling (TGARS 2021); Oct-MCNN-HS:3D Octave and 2D Vanilla Mixed Convolutional Neural Network for Hyperspectral Image Classification With Limited Samples (Remote Sensing, 2021)
PyTorch implementation of the paper - Revisiting Deep Hyperspectral Feature Extraction Networks via Gradient Centralized Convolution
Deep Matrix Capsules Implementation
Hyperspectral Image Classification, Feature Expansion, Multi-dimensional Information Expansion and Processing Network (MIEPN)
Compression and Reinforced Variation (CRV) Method
ACDFSL for Hyperspectral Image Classification
Random Shuffling Strategy, Siamese and Knowledge Distillation Network (SKDN), Hyperspectral Image Classification
Machine learning pipeline to classify hyperspectral images of fields.
Hyperspectral image classification lib in MATLAB.
This repository contains the necessary code to train PyTorch 2D-CNN models in Azure Machine Learning. Hyperspectral Imaging management is done to feed CNN models. When models are trained, their are registered in an Azure Machine Learning workspace, which are then used as a web service using Azure Kubernetes Service. These web service are used to classify brain hyperspectral images from raw images, providing classification maps with labeled tissues.
Bayesian CNN for HSI accuracy improvment
Hyperspectral Image Classification using Deep Transfer Learning