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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 101–150 of 286 papers

TitleStatusHype
Boosting Hyperspectral Image Classification with Gate-Shift-Fuse Mechanisms in a Novel CNN-Transformer Approach—0
Cascaded Recurrent Neural Networks for Hyperspectral Image Classification—0
Class-Wise Principal Component Analysis for hyperspectral image feature extraction—0
Combining multiscale features for classification of hyperspectral images: a sequence based kernel approach—0
Compressive spectral image classification using 3D coded convolutional neural network—0
Content-driven Magnitude-Derivative Spectrum Complementary Learning for Hyperspectral Image Classification—0
Cross-domain CNN for Hyperspectral Image Classification—0
Cross-Domain Collaborative Learning via Cluster Canonical Correlation Analysis and Random Walker for Hyperspectral Image Classification—0
Cross-View-Prediction: Exploring Contrastive Feature for Hyperspectral Image Classification—0
DCT-Mamba3D: Spectral Decorrelation and Spatial-Spectral Feature Extraction for Hyperspectral Image Classification—0
Deep Learning for Hyperspectral Image Classification: An Overview—0
Deep Learning Hyperspectral Image Classification Using Multiple Class-based Denoising Autoencoders, Mixed Pixel Training Augmentation, and Morphological Operations—0
Deep Neural Network Based Hyperspectral Pixel Classification With Factorized Spectral-Spatial Feature Representation—0
DiffSpectralNet : Unveiling the Potential of Diffusion Models for Hyperspectral Image Classification—0
Generating Hard Examples for Pixel-wise Classification—0
Discrete Wavelet Transform-Based Capsule Network for Hyperspectral Image Classification—0
Discriminative Robust Deep Dictionary Learning for Hyperspectral Image Classification—0
Does Normalization Methods Play a Role for Hyperspectral Image Classification?—0
Dual Classification Head Self-training Network for Cross-scene Hyperspectral Image Classification—0
DualMamba: A Lightweight Spectral-Spatial Mamba-Convolution Network for Hyperspectral Image Classification—0
Dynamic Memory-enhanced Transformer for Hyperspectral Image Classification—0
Effective training of deep convolutional neural networks for hyperspectral image classification through artificial labeling—0
ESW Edge-Weights : Ensemble Stochastic Watershed Edge-Weights for Hyperspectral Image Classification—0
Exploring Cross-Domain Pretrained Model for Hyperspectral Image Classification—0
Extreme Sparse Multinomial Logistic Regression: A Fast and Robust Framework for Hyperspectral Image Classification—0
Feature Extraction of Hyperspectral Images With Image Fusion and Recursive Filtering—0
Feature Selection and Classification of Hyperspectral Images With Support Vector Machines—0
Few-Shot Hyperspectral Image Classification With Unknown Classes Using Multitask Deep Learning—0
Forward-Forward Algorithm for Hyperspectral Image Classification: A Preliminary Study—0
Frost filtered scale-invariant feature extraction and multilayer perceptron for hyperspectral image classification—0
Fruit-HSNet: A Machine Learning Approach for Hyperspectral Image-Based Fruit Ripeness Prediction—0
GAF-NAU: Gramian Angular Field encoded Neighborhood Attention U-Net for Pixel-Wise Hyperspectral Image Classification—0
Generative Adversarial Networks and Probabilistic Graph Models for Hyperspectral Image Classification—0
Generative Adversarial Networks and Conditional Random Fields for Hyperspectral Image Classification—0
Generative Adversarial Networks Based on Transformer Encoder and Convolution Block for Hyperspectral Image Classification—0
Generative Adversarial Networks Based on Collaborative Learning and Attention Mechanism for Hyperspectral Image Classification—0
High Performance Hyperspectral Image Classification using Graphics Processing Units—0
Invariant Attribute Profiles: A Spatial-Frequency Joint Feature Extractor for Hyperspectral Image Classification—0
Is Pretraining Necessary for Hyperspectral Image Classification?—0
Kernel Extreme Learning Machine Optimized by the Sparrow Search Algorithm for Hyperspectral Image Classification—0
Kernel Task-Driven Dictionary Learning for Hyperspectral Image Classification—0
Label Consistent Transform Learning for Hyperspectral Image Classification—0
Ladder Networks for Semi-Supervised Hyperspectral Image Classification—0
Language-aware Domain Generalization Network for Cross-Scene Hyperspectral Image Classification—0
Language-Informed Hyperspectral Image Synthesis for Imbalanced-Small Sample Classification via Semi-Supervised Conditional Diffusion Model—0
Learning Hyperspectral Feature Extraction and Classification with ResNeXt Network—0
LiteDenseNet: A Lightweight Network for Hyperspectral Image Classification—0
LiteDepthwiseNet: An Extreme Lightweight Network for Hyperspectral Image Classification—0
Locality and Structure Regularized Low Rank Representation for Hyperspectral Image Classification—0
Modified Diversity of Class Probability Estimation Co-training for Hyperspectral Image Classification—0
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