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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 201–250 of 286 papers

TitleStatusHype
Structured Priors for Sparse-Representation-Based Hyperspectral Image Classification—0
Multiview Transformer: Rethinking Spatial Information in Hyperspectral Image Classification—0
WaveMamba: Spatial-Spectral Wavelet Mamba for Hyperspectral Image Classification—0
Naive Gabor Networks for Hyperspectral Image Classification—0
Objective Evaluation-based High-efficiency Learning Framework for Hyperspectral Image Classification—0
On the Sampling Strategy for Evaluation of Spectral-spatial Methods in Hyperspectral Image Classification—0
1D-Convolutional Capsule Network for Hyperspectral Image Classification—0
Parameter-Efficient Fine-Tuning of Multispectral Foundation Models for Hyperspectral Image Classification—0
Spatial-Spectral Feature Extraction via Deep ConvLSTM Neural Networks for Hyperspectral Image Classification—0
Physically-Constrained Transfer Learning through Shared Abundance Space for Hyperspectral Image Classification—0
Pixel DAG-Recurrent Neural Network for Spectral-Spatial Hyperspectral Image Classification—0
Predictive spectral analysis using an end-to-end deep model from hyperspectral images for high-throughput plant phenotyping—0
Task-Driven Dictionary Learning for Hyperspectral Image Classification with Structured Sparsity Constraints—0
Tensor Alignment Based Domain Adaptation for Hyperspectral Image Classification—0
ASPCNet: A Deep Adaptive Spatial Pattern Capsule Network for Hyperspectral Image Classification—0
Quantum-Inspired Spectral-Spatial Pyramid Network for Hyperspectral Image Classification—0
Randomized based restricted kernel machine for hyperspectral image classification—0
Randomized ICA and LDA Dimensionality Reduction Methods for Hyperspectral Image Classification—0
Randomized Principal Component Analysis for Hyperspectral Image Classification—0
Robust hyperspectral image classification with rejection fields—0
A Simplified 2D-3D CNN Architecture for Hyperspectral Image Classification Based on Spatial–Spectral Fusion—0
Row-Sparse Discriminative Deep Dictionary Learning for Hyperspectral Image Classification—0
An Ultralightweight Hybrid CNN Based on Redundancy Removal for Hyperspectral Image Classification—0
A novel statistical metric learning for hyperspectral image classification—0
Boosting the Generalization Ability for Hyperspectral Image Classification using Spectral-spatial Axial Aggregation Transformer—0
Segmentation-Aware Hyperspectral Image Classification—0
Selective Transformer for Hyperspectral Image Classification—0
Self Supervised Learning for Few Shot Hyperspectral Image Classification—0
A fast dynamic graph convolutional network and CNN parallel network for hyperspectral image classification—0
A fast and Accurate Similarity-constrained Subspace Clustering Framework for Unsupervised Hyperspectral Image Classification—0
Semi-supervised Hyperspectral Image Classification with Graph Clustering Convolutional Networks—0
Advances in Hyperspectral Image Classification: Earth monitoring with statistical learning methods—0
Semi-supervised Learning with Graphs: Covariance Based Superpixels For Hyperspectral Image Classification—0
WHU-Hi: UAV-borne hyperspectral with high spatial resolution (H2) benchmark datasets for hyperspectral image classification—0
Shallow Network Based on Depthwise Over-Parameterized Convolution for Hyperspectral Image Classification—0
Sharpend Cosine Similarity based Neural Network for Hyperspectral Image Classification—0
3DSS-Mamba: 3D-Spectral-Spatial Mamba for Hyperspectral Image Classification—0
Single-source Domain Expansion Network for Cross-Scene Hyperspectral Image Classification—0
SLCRF: Subspace Learning with Conditional Random Field for Hyperspectral Image Classification—0
HYPER-SNN: Towards Energy-efficient Quantized Deep Spiking Neural Networks for Hyperspectral Image Classification—0
TPPI-Net: Towards Efficient and Practical Hyperspectral Image Classification—0
Sparse Deformable Mamba for Hyperspectral Image Classification—0
Sparse Representation Based Augmented Multinomial Logistic Extreme Learning Machine with Weighted Composite Features for Spectral Spatial Hyperspectral Image Classification—0
DualMamba: A Lightweight Spectral-Spatial Mamba-Convolution Network for Hyperspectral Image Classification—0
Dual Classification Head Self-training Network for Cross-scene Hyperspectral Image Classification—0
Sparse Subspace Clustering Friendly Deep Dictionary Learning 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
Does Normalization Methods Play a Role for Hyperspectral Image Classification?—0
Adaptive Cross-Attention-Driven Spatial-Spectral Graph Convolutional Network for Hyperspectral Image Classification—0
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