Xiaoxu Li
Xiaoxu Li
Lanzhou University of Technology
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The devil is in the channels: Mutual-channel loss for fine-grained image classification
D Chang, Y Ding, J Xie, AK Bhunia, X Li, Z Ma, M Wu, J Guo, YZ Song
IEEE Transactions on Image Processing 29, 4683-4695, 2020
Dual cross-entropy loss for small-sample fine-grained vehicle classification
X Li, L Yu, D Chang, Z Ma, J Cao
IEEE Transactions on Vehicular Technology 68 (5), 4204-4212, 2019
Fine-grained vehicle classification with channel max pooling modified CNNs
Z Ma, D Chang, J Xie, Y Ding, S Wen, X Li, Z Si, J Guo
IEEE Transactions on Vehicular Technology 68 (4), 3224-3233, 2019
A concise review of recent few-shot meta-learning methods
X Li, Z Sun, JH Xue, Z Ma
Neurocomputing 456, 463-468, 2021
BSNet: Bi-similarity network for few-shot fine-grained image classification
X Li, J Wu, Z Sun, Z Ma, J Cao, JH Xue
IEEE Transactions on Image Processing 30, 1318-1331, 2020
Deep Metric Learning for Few-Shot Image Classification: A Review of Recent Developments
X Li, X Yang, Z Ma, JH Xue
Pattern Recognition, 109381, 2023
Image-text dual neural network with decision strategy for small-sample image classification
F Zhu, Z Ma, X Li, G Chen, JT Chien, JH Xue, J Guo
Neurocomputing 328, 182-188, 2019
Softmax cross entropy loss with unbiased decision boundary for image classification
J Cao, Z Su, L Yu, D Chang, X Li, Z Ma
2018 Chinese automation congress (CAC), 2028-2032, 2018
Large-margin regularized softmax cross-entropy loss
X Li, D Chang, T Tian, J Cao
IEEE access 7, 19572-19578, 2019
Learning calibrated class centers for few-shot classification by pair-wise similarity
Y Guo, R Du, X Li, J Xie, Z Ma, Y Dong
IEEE Transactions on Image Processing 31, 4543-4555, 2022
Oslnet: Deep small-sample classification with an orthogonal softmax layer
X Li, D Chang, Z Ma, ZH Tan, JH Xue, J Cao, J Yu, J Guo
IEEE Transactions on Image Processing 29, 6482-6495, 2020
Supervised latent Dirichlet allocation with a mixture of sparse softmax
X Li, Z Ma, P Peng, X Guo, F Huang, X Wang, J Guo
Neurocomputing 312, 324-335, 2018
Amortized bayesian prototype meta-learning: A new probabilistic meta-learning approach to few-shot image classification
Z Sun, J Wu, X Li, W Yang, JH Xue
International Conference on Artificial Intelligence and Statistics, 1414-1422, 2021
ReMarNet: Conjoint relation and margin learning for small-sample image classification
X Li, L Yu, X Yang, Z Ma, JH Xue, J Cao, J Guo
IEEE Transactions on Circuits and Systems for Video Technology 31 (4), 1569-1579, 2020
Deep InterBoost networks for small-sample image classification
X Li, D Chang, Z Ma, ZH Tan, JH Xue, J Cao, J Guo
Neurocomputing 456, 492-503, 2021
Bi-directional feature reconstruction network for fine-grained few-shot image classification
J Wu, D Chang, A Sain, X Li, Z Ma, J Cao, J Guo, YZ Song
Proceedings of the AAAI Conference on Artificial Intelligence 37 (3), 2821-2829, 2023
CC-loss: Channel correlation loss for image classification
Z Song, D Chang, Z Ma, X Li, ZH Tan
2020 25th International Conference on Pattern Recognition (ICPR), 7601-7608, 2021
ReNAP: Relation network with adaptiveprototypical learning for few-shot classification
X Li, Y Li, Y Zheng, R Zhu, Z Ma, JH Xue, J Cao
Neurocomputing 520, 356-364, 2023
TLRM: Task-level relation module for GNN-based few-shot learning
Y Guo, Z Ma, X Li, Y Dong
2021 International Conference on Visual Communications and Image Processing …, 2021
Channel max pooling layer for fine-grained vehicle classification
Z Ma, D Chang, X Li
arXiv preprint arXiv:1902.11107, 2019
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