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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 76–100 of 286 papers

TitleStatusHype
Classification of Hyperspectral Images Using SVM with Shape-adaptive Reconstruction and Smoothed Total VariationCode0
Multiscale Principle of Relevant Information for Hyperspectral Image ClassificationCode0
Multi-level Relation Learning for Cross-domain Few-shot Hyperspectral Image ClassificationCode0
BS-Nets: An End-to-End Framework For Band Selection of Hyperspectral ImageCode0
Bridging Sensor Gaps via Attention Gated Tuning for Hyperspectral Image ClassificationCode0
Multi-head Spatial-Spectral Mamba for Hyperspectral Image ClassificationCode0
Boosting with Lexicographic Programming: Addressing Class Imbalance without Cost TuningCode0
BASS Net: Band-Adaptive Spectral-Spatial Feature Learning Neural Network for Hyperspectral Image ClassificationCode0
Local Low-Rank Approximation With Superpixel-Guided Locality Preserving Graph for Hyperspectral Image ClassificationCode0
Efficient Dynamic Attention 3D Convolution for Hyperspectral Image ClassificationCode0
MOB-GCN: A Novel Multiscale Object-Based Graph Neural Network for Hyperspectral Image ClassificationCode0
Multi-scale Dynamic Graph Convolutional Network for Hyperspectral Image ClassificationCode0
Hyperspectral Image Classification With Contrastive Graph Convolutional NetworkCode0
Dynamic 3D KAN Convolution with Adaptive Grid Optimization for Hyperspectral Image ClassificationCode0
Augmenting Prototype Network with TransMix for Few-shot Hyperspectral Image ClassificationCode0
Importance of Disjoint Sampling in Conventional and Transformer Models for Hyperspectral Image ClassificationCode0
Hyperspectral image classification via a random patches networkCode0
A Universal Knowledge Embedded Contrastive Learning Framework for Hyperspectral Image ClassificationCode0
3D-Convolution Guided Spectral-Spatial Transformer for Hyperspectral Image ClassificationCode0
Hyperspectral Image Classification via Sparse Representation With Incremental DictionariesCode0
Hyperspectral Image Classification via Transformer-based Spectral-Spatial Attention Decoupling and Adaptive GatingCode0
Hyperspectral Image Classification with Markov Random Fields and a Convolutional Neural NetworkCode0
Expert Kernel Generation Network Driven by Contextual Mapping for Hyperspectral Image ClassificationCode0
Hyperspectral Image Classification: Artifacts of Dimension Reduction on Hybrid CNNCode0
Discrete Cosine Transform-Based Joint Spectral-Spatial Information Compression and Band Correlation Calculation for Hyperspectral Feature ExtractionCode0
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