PyTorch implementation of the paper - Revisiting Deep Hyperspectral Feature Extraction Networks via Gradient Centralized Convolution
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Updated
Mar 15, 2022 - Jupyter Notebook
PyTorch implementation of the paper - Revisiting Deep Hyperspectral Feature Extraction Networks via Gradient Centralized Convolution
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…
《SGT: A Generalized Processing Model for 1-D Remote Sensing Signal Classification》
ACDFSL for Hyperspectral Image Classification
Hyperspectral Image Classification using Deep Transfer Learning
Bayesian CNN for HSI accuracy improvment
Hyperspectral image classification lib in MATLAB.
Compression and Reinforced Variation (CRV) Method
Random Shuffling Strategy, Siamese and Knowledge Distillation Network (SKDN), Hyperspectral Image Classification
Parallel Multi-Input Mechanism-Based Convolutional Neural Network
Hyperspectral Image Classification, Feature Expansion, Multi-dimensional Information Expansion and Processing Network (MIEPN)
Machine learning pipeline to classify hyperspectral images of fields.
Deep Matrix Capsules Implementation
This is the code of the paper Multiple Spectral Resolution 3D Convolutional Neural Network for Hyperspectral Image Classification. And the paper has been accpeted by remote sensing.
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 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.
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