Hyperspectral Image Classification

Photon Neural Network Achieves ‘In-Sensor Imaging Classification’, Paving the Way for Technological Innovations in Autonomous Driving and Security Fields

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Photon Neural Network Achieves 'In-Sensor Imaging Classification', Paving the Way for Technological Innovations in Autonomous Driving and Security Fields

In the visual perception systems of autonomous driving, the massive image data captured by sensors must be transmitted to processors for processing. This process not only generates redundant data but also causes delays, which may affect decision-making in emergencies. Similarly, in the field of security monitoring, real-time image classification faces bottlenecks in data transmission and … Read more

MaxViT: Multi-Axis Vision Transformer

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MaxViT: Multi-Axis Vision Transformer

Click the blue text above to follow us MaxViT: Multi-Axis Vision TransformerZhengzhong Tu, Hossein TalebiComments: ECCV 2022[v1] Mon, 4 Apr 2022 17:59:44 UTC (235 KB)https://github.com/google-research/maxvitby Z Tu · 2022 · Cited by 1045 This paper proposes a multi-axis vision Transformer architecture called MaxViT, which innovatively reduces the computational complexity from quadratic to linear through a … Read more

A Synergistic CNN-Transformer Network with Pooling Attention Fusion for Hyperspectral Image Classification

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A Synergistic CNN-Transformer Network with Pooling Attention Fusion for Hyperspectral Image Classification

Title: A synergistic CNN-transformer network with pooling attention fusion for hyperspectral image classification Paper link: https://github.com/chenpeng052/SCT-Net HPA (Hybrid Pooling Attention) Hybrid Pooling Attention: Divides channels into groups and performs global average pooling and global max pooling in both horizontal and vertical directions, followed by a 1×11 imes11×1 convolution and Sigmoid to obtain channel attention; simultaneously, … Read more

A Synergistic CNN-Transformer Network with Pooling Attention Fusion for Hyperspectral Image Classification

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A Synergistic CNN-Transformer Network with Pooling Attention Fusion for Hyperspectral Image Classification

Title:A synergistic CNN-transformer network with pooling attention fusion for hyperspectral image classification Paper Link: https://www.sciencedirect.com/science/article/abs/pii/S1051200425000922 Two-Branch Feature Extraction Module (TBFE): Utilizes 2D and 3D convolutions in parallel to extract spatial and spectral features, effectively fusing multidimensional information. Hybrid Pooling Attention Module (HPA): Combines average pooling and max pooling to achieve information aggregation across spatial dimensions, … Read more

TBFE: Twin-Branch Feature Extraction Module for Hyperspectral Image Classification

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TBFE: Twin-Branch Feature Extraction Module for Hyperspectral Image Classification

Title:A synergistic CNN-transformer network with pooling attention fusion for hyperspectral image classification Paper Link: https://www.sciencedirect.com/science/article/abs/pii/S1051200425000922?via%3Dihub TBFE (Twin-Branch Feature Extraction): A parallel fusion of 2D and 3D convolutions, used to extract spatial and spectral features respectively. HPA (Hybrid Pooling Attention): A designed attention mechanism that combines average pooling and max pooling to enhance channel representation in … Read more

A Synergistic CNN-Transformer Network with Pooling Attention Fusion for Hyperspectral Image Classification

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A Synergistic CNN-Transformer Network with Pooling Attention Fusion for Hyperspectral Image Classification

Title:A synergistic CNN-transformer network with pooling attention fusion for hyperspectral image classification Paper Link: https://www.sciencedirect.com/science/article/abs/pii/S1051200425000922 Proposed synergistic CNN-Transformer network, combining the local feature extraction capability of CNNs with the global modeling advantages of Transformers, while processing the spatial and spectral information of HSI. Designed Two-Branch Feature Extraction (TBFE) module, which utilizes 3D convolution (focusing on … Read more

DSP 2025: Plug-and-Play Fusion Pooling Attention Mechanism, Continuously Open Source

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DSP 2025: Plug-and-Play Fusion Pooling Attention Mechanism, Continuously Open Source

Title:A synergistic CNN-transformer network with pooling attention fusion for hyperspectral image classification Paper Link:https://doi.org/10.1016/j.dsp.2025.105070 Collaborative CNN-Transformer Architecture Design A synergistic CNN-Transformer network is proposed, combining the local spatial feature extraction capability of CNNs with the global modeling capability of Transformers, effectively achieving joint modeling of spectral and spatial information in hyperspectral images (HSI). Two-Branch Feature … Read more

(DSP 2025) Hyperspectral Image Classification Module: Plug-and-Play and Completely Crazy

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(DSP 2025) Hyperspectral Image Classification Module: Plug-and-Play and Completely Crazy

Title:A synergistic CNN-transformer network with pooling attention fusion for hyperspectral image classification Paper link: https://doi.org/10.1016/j.dsp.2025.105070 1. Proposed Synergistic CNN-Transformer Network Structure: Combines the local spatial feature extraction capabilities of CNNs with the global spectral modeling capabilities of Transformers to comprehensively extract spatial-spectral features from hyperspectral images (HSI).2. Twin-Branch Feature Extraction Module (TBFE): Parallel combination of … Read more