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Hyperspectral Image Classification

Hyperspectral Image Classification is a task in the field of remote sensing and computer vision. It involves the classification of pixels in hyperspectral images into different classes based on their spectral signature. Hyperspectral images contain information about the reflectance of objects in hundreds of narrow, contiguous wavelength bands, making them useful for a wide range of applications, including mineral mapping, vegetation analysis, and urban land-use mapping. The goal of this task is to accurately identify and classify different types of objects in the image, such as soil, vegetation, water, and buildings, based on their spectral properties.

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

Papers

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Showing 51–75 of 286 papers

TitleStatusHype
Adaptive Mask Sampling and Manifold to Euclidean Subspace Learning with Distance Covariance Representation for Hyperspectral Image ClassificationCode1
Dual-stage Hyperspectral Image Classification Model with Spectral SupertokenCode1
SpectralFormer: Rethinking Hyperspectral Image Classification with TransformersCode1
SpectralNET: Exploring Spatial-Spectral WaveletCNN for Hyperspectral Image ClassificationCode1
A Fast 3D CNN for Hyperspectral Image ClassificationCode1
Spectral-Spatial Transformer with Active Transfer Learning for Hyperspectral Image ClassificationCode1
Semisupervised Cross-scale Graph Prototypical Network for Hyperspectral Image ClassificationCode1
Triplet-Watershed for Hyperspectral Image ClassificationCode1
Efficient Deep Learning of Non-local Features for Hyperspectral Image ClassificationCode1
HyperKAN: Kolmogorov-Arnold Networks make Hyperspectral Image Classificators SmarterCode1
Deep Reinforcement Learning for Band Selection in Hyperspectral Image ClassificationCode1
Grafting Transformer on Automatically Designed Convolutional Neural Network for Hyperspectral Image ClassificationCode1
Deep Prototypical Networks with Hybrid Residual Attention for Hyperspectral Image ClassificationCode1
Dual-Branch Subpixel-Guided Network for Hyperspectral Image ClassificationCode1
Faster hyperspectral image classification based on selective kernel mechanism using deep convolutional networksCode1
DCN-T: Dual Context Network with Transformer for Hyperspectral Image ClassificationCode1
A2S-NAS: Asymmetric Spectral-Spatial Neural Architecture Search For Hyperspectral Image Classification—0
A novel statistical metric learning for hyperspectral image classification—0
Effective training of deep convolutional neural networks for hyperspectral image classification through artificial labeling—0
Content-driven Magnitude-Derivative Spectrum Complementary Learning for Hyperspectral Image Classification—0
Compressive spectral image classification using 3D coded convolutional neural network—0
A fast dynamic graph convolutional network and CNN parallel network for hyperspectral image classification—0
Combining multiscale features for classification of hyperspectral images: a sequence based kernel approach—0
Class-Wise Principal Component Analysis for hyperspectral image feature extraction—0
A fast and Accurate Similarity-constrained Subspace Clustering Framework for Unsupervised Hyperspectral Image Classification—0
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