A Hybrid Transformer for Hyperspectral Image Classification

A hybrid transformer that integrates multigranularity tokens and spatial–spectral attention (SSA) is proposed.

A hybrid convolution transformer for hyperspectral image classification

We propose a hybrid convolution transformer framework. Our method uses a vision transformer and a residual 3D convolutional neural network model.

Hybrid Vision Transformer Model for Hyperspectral Image ...

Therefore, a large number of CNN-based methods are introduced to hyperspectral image (HSI) classification. However, receptive fields of these methods are ...

(PDF) Hybrid Vision Transformer Model for Hyperspectral Image ...

PDF | On Jul 17, 2022, Jiaqi Yang and others published Hybrid Vision Transformer Model for Hyperspectral Image Classification | Find, read and cite all the ...

A hybrid convolution transformer for hyperspectral image classification

PDF | Hyperspectral images play a crucial role in remote sensing applications surveillance, environment and precision agriculture, ...

zhaolin6/HybridFormer - GitHub

... Spectral Attention: A Hybrid Transformer for Hyperspectral Image Classification (HybridFormer). This is an official pytorch implementation of HybridFormer ...

State space models meet transformers for hyperspectral image ...

The first work to explore State-Space-Model based method for hyperspectral remote sensing image classification task. •. A novel SSM-Transformer hybrid model ...

Hyperspectral Image Classification via Spectral Pooling and Hybrid ...

Therefore, many joint CNN and Transformer architectures for HSI classification have been proposed to obtain the merits of both networks. However, these ...

When Multigranularity Meets Spatial–Spectral Attention: A Hybrid ...

When Multigranularity Meets Spatial–Spectral Attention: A Hybrid Transformer for Hyperspectral Image Classification · E. Ouyang, Bin Li, +3 authors. Jianhui Wu ...

Mayukh-Mondal-Dev/Hybrid-SSRN-Vision-Transformer-Architecture ...

In this project, we propose a hyperspectral image classification method that combines the strengths of Vision Transformers and Convolutional Neural Networks ( ...

Spectral Transformer for Hyperspectral Image Classification Based ...

We propose a novel solution: the multi-scale spatial–spectral transformer (MSST). Within the MSST framework, we introduce a spatial–spectral token generator ( ...

Convolutional Meets Transformer Network for Hyperspectral Images ...

Existing HSI classification methods based on CNN-Transformer hybrid architectures [25] usually adopt manually specified hybrid strategies ...

HyFormer: Hybrid Transformer and CNN for Pixel-Level ...

[30,31,32,33,34,35,36,37] focused on using graph neural networks to achieve hyperspectral image classification, solving the problems of graph ...

GroupFormer for hyperspectral image classification through group ...

We proposed a spectral-spatial feature extractor group attention transformer that consists of a multiscale feature extractor to extract low-level or shallow ...

Hybrid Conv-ViT Network for Hyperspectral Image Classification

A hybrid convolution and ViT network (HCVN) is proposed for HSI classification, which enhances the ability of local structure characterization while ...

Graph-infused hybrid vision transformer: Advancing GeoAI for ...

Hyperspectral Image Classification (HSIC) is a challenging task due to the high-dimensional nature of Hyperspectral Imaging (HSI) data and the complex ...

A Hybrid Self-supervised Learning Framework For Hyperspectral ...

Masked auto-encoding spectral–spatial transformer for hyperspectral image classification. IEEE Transactions on Geoscience and Remote Sensing ...

Hyperspectral Image Classification via Spectral Pooling and Hybrid ...

To address this problem, we propose a neighborhood enhancement hybrid transformer (NEHT) network. In particular, a simple 2D convolution module is adopted to ...

Full article: Spectral Spatial Neighborhood Attention Transformer for ...

Hyperspectral image classification (HSI) is a part of earth observation extensively used in agriculture, physics, astronomy, chemical imaging, and environmental ...

A Comprehensive Survey for Hyperspectral Image Classification

Spatial-Spectral Feature; Hyperspectral Image Classification (HSC); Convolutional Neural Networks (CNNs); Spatial-Spectral Transformers (SSTs); ...