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Nengjun Yang
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2020 – today
- 2023
- [j9]Zhili Zhang, Yao Ding
, Xiaofeng Zhao, Siye Li, Nengjun Yang, Yaoming Cai
Multireceptive field: An adaptive path aggregation graph neural framework for hyperspectral image classification. Expert Syst. Appl. 217: 119508 (2023) - [j8]Yao Ding
Multi-scale receptive fields: Graph attention neural network for hyperspectral image classification. Expert Syst. Appl. 223: 119858 (2023) - 2022
- [j7]Yao Ding
Multi-feature fusion: Graph neural network and CNN combining for hyperspectral image classification. Neurocomputing 501: 246-257 (2022) - [j6]Yao Ding
Graph Sample and Aggregate-Attention Network for Hyperspectral Image Classification. IEEE Geosci. Remote. Sens. Lett. 19: 1-5 (2022) - [j5]Yao Ding
Unsupervised Self-Correlated Learning Smoothy Enhanced Locality Preserving Graph Convolution Embedding Clustering for Hyperspectral Images. IEEE Trans. Geosci. Remote. Sens. 60: 1-16 (2022) - [j4]Yao Ding
Semi-Supervised Locality Preserving Dense Graph Neural Network With ARMA Filters and Context-Aware Learning for Hyperspectral Image Classification. IEEE Trans. Geosci. Remote. Sens. 60: 1-12 (2022) - 2021
- [j3]Shaohua Huang
A weighted fuzzy C-means clustering method with density peak for anomaly detection in IoT-enabled manufacturing process. J. Intell. Manuf. 32(7): 1845-1861 (2021) - [j2]Yao Ding
Multiscale Graph Sample and Aggregate Network With Context-Aware Learning for Hyperspectral Image Classification. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 14: 4561-4572 (2021) - 2020
- [j1]Weiguang Fang, Yu Guo, Wenhe Liao, Shaohua Huang
A Parallel Gated Recurrent Units (P-GRUs) network for the shifting lateness bottleneck prediction in make-to-order production system. Comput. Ind. Eng. 140: 106246 (2020)
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