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Graph Neural Network for Feature Extraction and Classification of Hyperspectral Remote Sensing Images / / by Yao Ding, Zhili Zhang, Haojie Hu, Fang He, Shuli Cheng, Yijun Zhang
| Graph Neural Network for Feature Extraction and Classification of Hyperspectral Remote Sensing Images / / by Yao Ding, Zhili Zhang, Haojie Hu, Fang He, Shuli Cheng, Yijun Zhang |
| Autore | Ding Yao |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (189 pages) |
| Disciplina | 621.382 |
| Altri autori (Persone) |
ZhangZhili
HuHaojie HeFang ChengShuli ZhangYijun |
| Collana | Intelligent Perception and Information Processing |
| Soggetto topico |
Image processing
Neural networks (Computer science) Machine learning Image Processing Mathematical Models of Cognitive Processes and Neural Networks Machine Learning |
| ISBN |
9789819780099
9819780098 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Graph sample and aggregate-attention network for hyperspectral image classification -- Multi-feature fusion: Graph neural network and CNN combining for hyperspectral image classification -- Pixel and hyperpixel level feature combining for hyperspectral image classification -- Global dynamic graph optimization for hyperspectral image classification -- Exploring relationship between transformer and graph convolution for hyperspectral image classification. |
| Record Nr. | UNINA-9910910493103321 |
Ding Yao
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Graph Neural Network for Hyperspectral Image Clustering / / by Yao Ding, Zhili Zhang, Haojie Hu, Renxiang Guan, Jie Feng, Zhiyong Lv
| Graph Neural Network for Hyperspectral Image Clustering / / by Yao Ding, Zhili Zhang, Haojie Hu, Renxiang Guan, Jie Feng, Zhiyong Lv |
| Autore | Ding Yao |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (259 pages) |
| Disciplina | 621.382 |
| Altri autori (Persone) |
ZhangZhili
HuHaojie GuanRenxiang FengJie LvZhiyong |
| Collana | Intelligent Perception and Information Processing |
| Soggetto topico |
Image processing
Medicine - Research Biology - Research Neural networks (Computer science) Machine learning Image Processing Biomedical Research Mathematical Models of Cognitive Processes and Neural Networks Machine Learning |
| ISBN | 981-9677-10-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Self-supervised Efficient Low-pass Contrastive Graph Clustering for Hyperspectral Images -- Self-Supervised Locality Preserving Low-Pass Graph Convolutional Embedding for Large-Scale Hyperspectral Image Clustering -- Adaptive Homophily Clustering: A Structure Homophily Graph Learning with Adaptive Filter for Hyperspectral Image -- Pixel-superpixel Contrastive Learning And Pseudo-label correction For Hyperspectral Image Clustering -- Contrastive Multiview Subspace Clustering of Hyperspectral Images Based on Graph Convolutional Networks. |
| Record Nr. | UNINA-9911020416403321 |
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Ding Yao
|
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||