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A novel spectral–spatial wave network for hyperspectral image ...


A novel spectral–spatial wave network for hyperspectral image ...

This paper proposes a novel spectral–spatial wave network (S WaveNet) for HSI classification tasks to enhance the representation capability of spectral–spatial ...

S 2 WaveNet: A novel spectral–spatial wave network for ...

Request PDF | On Apr 1, 2024, Yanan Jiang and others published S 2 WaveNet: A novel spectral–spatial wave network for hyperspectral image classification ...

SSFN: a novel Spatial-Spectral FusionNet for hyperspectral image ...

Hyperspectral image classification is the process of identifying ground objects within hyperspectral images at the pixel level. While many CNN based methods ...

SSFN: a novel Spatial-Spectral FusionNet for hyperspectral image ...

Waves Random Media (1991 - 2004) ... [5] Li Ying et al Spectral-Spatial Classification of Hyperspectral Imagery with 3D Convolutional Neural Network (2022).

(PDF) Spectral-Spatial Attention Network for Hyperspectral Image ...

PDF | Hyperspectral image (HSI) classification aims to assign each hyperspectral pixel with a proper land-cover label. Recently, convolutional neural.

Hyperspectral image classification using spectral-spatial LSTMs

In this paper, we propose a hyperspectral image (HSI) classification method using spectral-spatial long short term memory (LSTM) networks.

Spatial-Spectral Residual Network for Hyperspectral Image Super ...

In this paper, we propose a novel spectral-spatial residual network for hyperspectral image super-resolution (SSRNet).

Spectral–Spatial Feature Extraction for Hyperspectral Image ... - OUCI

In the hyperspectral image (HSI) classification task, every HSI pixel is labeled as a specific land cover category. Although convolutional neural network ...

Deep Spectral Spatial Inverted Residual Network for Hyperspectral ...

Convolutional neural networks (CNNs) have been widely used in hyperspectral image classification in recent years. The training of CNNs relies on a large ...

Discriminating Spectral–Spatial Feature Extraction for Hyperspectral ...

A general generative adversarial capsule network for hyperspectral image spectral–spatial classification. Remote Sens. Lett. 2020, 11, 19–28. [Google ...

Hyperspectral Imagery Spatial Super-Resolution Using Generative ...

In this paper, we propose a novel Hyperspectral imagery Spatial. Super-Resolution algorithm based on a Generative Adversarial. Network (HSSRGAN). The generator ...

Unsupervised Spatial–Spectral Network Learning for Hyperspectral ...

An unsupervised spatial–spectral network to reconstruct HSIs only from the compressive snapshot measurement is proposed, which acts as a conditional ...

Quantum-Inspired Spectral-Spatial Pyramid Network for ...

Hyperspectral image (HSI) classification aims at assign- ing a unique label for every pixel to identify categories of different land covers.

A novel spatial and spectral transformer network for hyperspectral ...

Recently, transformer networks based on hyperspectral image super-resolution have achieved significant performance in comparison with most.

[2406.07050] DualMamba: A Lightweight Spectral-Spatial Mamba ...

DualMamba: A Lightweight Spectral-Spatial Mamba-Convolution Network for Hyperspectral Image Classification. Authors:Jiamu Sheng, Jingyi Zhou, ...

International Space Station - NASA

NASA astronauts Andrew Feustel and Ricky Arnold and Roscosmos cosmonaut Oleg Artemyev executed a fly around of the orbiting laboratory to take pictures of the ...

A novel meta-learning-based hyperspectral image classification ...

[8] designed a spectral–spatial residual network (SSRN) to identify HSI spectral properties and spatial context using spectral and spatial ...

Volume 635 Issue 8037, 7 November 2024 - Nature

... network of ancient ... A broadband hyperspectral image sensor fabricated using photolithography maintains high throughput with high spatial ...

27 Fully Funded PhD Programs at Queen's University Belfast ...

... imaging applications in the sub-millimeter wave region. ... Fully Funded PhD Position in Self-supervised summarisation of hyperspectral image data.