Moving object detection method via ResNet-18 with encoder–decoder structure in complex scenes X Ou, P Yan, Y Zhang, B Tu, G Zhang, J Wu, W Li IEEE Access 7, 108152-108160, 2019 | 125 | 2019 |
KNN-based representation of superpixels for hyperspectral image classification B Tu, J Wang, X Kang, G Zhang, X Ou, L Guo IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2018 | 102 | 2018 |
Hyperspectral image classification via fusing correlation coefficient and joint sparse representation B Tu, X Zhang, X Kang, G Zhang, J Wang, J Wu IEEE Geoscience and Remote Sensing Letters 15 (3), 340-344, 2018 | 97 | 2018 |
Spatial density peak clustering for hyperspectral image classification with noisy labels B Tu, X Zhang, X Kang, J Wang, JA Benediktsson IEEE Transactions on Geoscience and Remote Sensing 57 (7), 5085-5097, 2019 | 90 | 2019 |
Hyperspectral classification with noisy label detection via superpixel-to-pixel weighting distance B Tu, C Zhou, D He, S Huang, A Plaza IEEE Transactions on Geoscience and Remote Sensing 58 (6), 4116-4131, 2020 | 87 | 2020 |
Density peak-based noisy label detection for hyperspectral image classification B Tu, X Zhang, X Kang, G Zhang, S Li IEEE Transactions on Geoscience and Remote Sensing 57 (3), 1573-1584, 2018 | 82 | 2018 |
Local semantic feature aggregation-based transformer for hyperspectral image classification B Tu, X Liao, Q Li, Y Peng, A Plaza IEEE Transactions on Geoscience and Remote Sensing 60, 1-15, 2022 | 78 | 2022 |
Hyperspectral anomaly detection via density peak clustering B Tu, X Yang, N Li, C Zhou, D He Pattern Recognition Letters 129, 144-149, 2020 | 78 | 2020 |
Spatial–spectral transformer with cross-attention for hyperspectral image classification Y Peng, Y Zhang, B Tu, Q Li, W Li IEEE Transactions on Geoscience and Remote Sensing 60, 1-15, 2022 | 66 | 2022 |
A CNN framework with slow-fast band selection and feature fusion grouping for hyperspectral image change detection X Ou, L Liu, B Tu, G Zhang, Z Xu IEEE transactions on geoscience and remote sensing 60, 1-16, 2022 | 64 | 2022 |
Spectral–spatial hyperspectral classification via structural-kernel collaborative representation B Tu, C Zhou, X Liao, G Zhang, Y Peng IEEE Geoscience and Remote Sensing Letters 18 (5), 861-865, 2020 | 60 | 2020 |
Multiple convolutional layers fusion framework for hyperspectral image classification G Zhao, G Liu, L Fang, B Tu, P Ghamisi Neurocomputing 339, 149-160, 2019 | 55 | 2019 |
Hyperspectral image classification via weighted joint nearest neighbor and sparse representation B Tu, S Huang, L Fang, G Zhang, J Wang, B Zheng IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2018 | 54 | 2018 |
Hyperspectral imagery noisy label detection by spectral angle local outlier factor B Tu, C Zhou, W Kuang, L Guo, X Ou IEEE Geoscience and Remote Sensing Letters 15 (9), 1417-1421, 2018 | 54 | 2018 |
NCGLF2: Network combining global and local features for fusion of multisource remote sensing data B Tu, Q Ren, J Li, Z Cao, Y Chen, A Plaza Information Fusion 104, 102192:1-17, 2024 | 53 | 2024 |
Hyperspectral anomaly detection using dual window density B Tu, X Yang, C Zhou, D He, A Plaza IEEE Transactions on Geoscience and Remote Sensing 58 (12), 8503-8517, 2020 | 49 | 2020 |
Cuckoo search algorithm with fuzzy logic and Gauss–Cauchy for minimizing localization error of WSN X Ou, M Wu, Y Pu, B Tu, G Zhang, Z Xu Applied Soft Computing 125, 109211, 2022 | 47 | 2022 |
Hyperspectral anomaly detection using reconstruction fusion of quaternion frequency domain analysis B Tu, X Yang, W He, J Li, A Plaza IEEE Transactions on Neural Networks and Learning Systems, 2023 | 44 | 2023 |
Class-wise graph embedding-based active learning for hyperspectral image classification X Liao, B Tu, J Li, A Plaza IEEE Transactions on Geoscience and Remote Sensing 61, 5522813: 1-13, 2023 | 38 | 2023 |
Multi-objective unsupervised band selection method for hyperspectral images classification X Ou, M Wu, B Tu, G Zhang, W Li IEEE Transactions on Image Processing 32, 1952-1965, 2023 | 38 | 2023 |