Past Selected Conference Publications

• Yang, S., Li, X., Chang, D., Ma, Z. and Xue, J.-H. (2024) Channel-spatial support-query cross-attention for fine-grained few-shot image classification. ACM International Conference on Multimedia (ACM MM, acceptance rate 26.2%), 9175-9183.
• Xia, W., de Charette, R., Öztireli, C. and Xue, J.-H. (2024) UMBRAE: Unified multimodal brain decoding. European Conference on Computer Vision (ECCV, acceptance rate 27.9%), 242-259.
• Yan, S., Qiu, X., Liao, Q., Xue, J.-H. and Liu, S. (2024) Reschedule diffusion-based bokeh rendering. International Joint Conference on Artificial Intelligence (IJCAI, acceptance rate 14.0%), 1543-1551.
• Zhang, Z., Yan, Y., Xue, J.-H. and Wang, H. (2024) Spatial-contextual discrepancy information compensation for GAN inversion. AAAI Conference on Artificial Intelligence (AAAI, acceptance rate 23.75%), 38(7), 7432-7440.
• Qiu, L., Chen, S., Yan, Y., Xue, J.-H., Wang, D.-H.. and Zhu, S. (2024) High-order structure based middle-feature learning for visible-infrared person re-identification. AAAI Conference on Artificial Intelligence (AAAI, acceptance rate 23.75%), 38(5), 4596-4604.
• Xia, W., de Charette, R., Öztireli, C. and Xue, J.-H. (2024) DREAM: Visual decoding from reversing human visual system. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV, acceptance rate 41.5%), 8226-8235.
• Wang, H., Xiang, X., Fan, Y. and Xue, J.-H. (2024) Customizing 360-degree panoramas through text-to-image diffusion models. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV, acceptance rate 41.5%), 4933-4943.
• Zou, X., Yan, Y., Xue, J.-H., Chen, S. and Wang, H. (2022) Learn-to-decompose: Cascaded decomposition network for cross-domain few-shot facial expression recognition. European Conference on Computer Vision (ECCV, acceptance rate 28%), 683-700.
• Ling, Y. and Xue, J.-H. (2022) Dimension reduction for high-dimensional small counts with KL divergence. Conference on Uncertainty in Artificial Intelligence (UAI, acceptance rate 32.3%), PMLR 180, 1210-1220.
• Zou, X., Yan, Y., Xue, J.-H., Chen, S. and Wang, H. (2022) When facial expression recognition meets few-shot learning: A joint and alternate learning framework. AAAI Conference on Artificial Intelligence (AAAI, acceptance rate 15%), 36(5), 5367-5375.
• Shen, X., Lu, Z., Zhang, Y. and Xue, J.-H. (2021) Lane line detection based on parallel spatial separation convolution. British Machine Vision Conference (BMVC, acceptance rate (Oral) 3.3%).
• Xiao, Z., Xue, J.-H., Xie, P. and Wang, G. (2021) FETNet: Feature exchange transformer network for RGB-D object detection. British Machine Vision Conference (BMVC, acceptance rate 36.2%).
• Mo, R., Yan, Y., Xue, J.-H., Chen, S. and Wang, H. (2021) D³Net: Dual-branch disturbance disentangling network for facial expression recognition. ACM International Conference on Multimedia (ACM MM, acceptance rate 27.9%), 779-787.
• Zhou, C., Lu, Z., Li, L., Yan, Q. and Xue, J.-H. (2021) How video super-resolution and frame interpolation mutually benefit. ACM International Conference on Multimedia (ACM MM, acceptance rate 27.9%), 5445-5453.
• Xu, Y., Yan, Y., Xue, J.-H., Lu, Y. and Wang, H. (2021) Small-vote sample selection for label-noise learning. Joint European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD, acceptance rate 21%), 729-744.
• Ling, Y., Liu, Z. and Xue, J.-H. (2021) Dimension reduction for data with heterogeneous missingness. Conference on Uncertainty in Artificial Intelligence (UAI, acceptance rate 26.5%), PMLR 161, 1310-1320.
• Liu, L., Zhang, S., Kuang, Z., Xue, J.-H., Zhou, A., Wang, X., Chen, Y., Yang, W., Liao, Q. and Zhang, W. (2021) Group Fisher pruning for practical network compression. International Conference on Machine Learning (ICML, acceptance rate 21.5%), PMLR 139, 7021-7032.
• Xia, W., Yang, Y., Xue, J.-H. and Wu, B. (2021) TediGAN: Text-guided diverse face image generation and manipulation. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR, acceptance rate 23.7%), 2256-2265.
• Shu, Y., Yan, Y., Chen, S., Xue, J.-H., Shen, C. and Wang, H. (2021) Learning spatial-semantic relationship for facial attribute recognition with limited labeled data. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR, acceptance rate 23.7%), 11916-11925.
• Sun, Z., Wu, J., Li, X., Yang, W. and Xue, J.-H. (2021) Amortized Bayesian prototype meta-learning: A new probabilistic meta-learning approach to few-shot image classification. International Conference on Artificial Intelligence and Statistics (AISTATS, acceptance rate 29.8%), PMLR 130, 1414-1422.
• Liu, L., Li, Y., Kuang, Z., Xue, J.-H., Chen, Y., Yang, W., Liao, Q. and Zhang, W. (2021) Towards impartial multi-task learning. International Conference on Learning Representations (ICLR, acceptance rate 28.7%).
• Dong, M., Yang, X., Zhu, R., Wang, Y. and Xue, J.-H. (2020) Generalization bound of gradient descent for non-convex metric learning. Advances in Neural Information Processing Systems (NeurIPS, acceptance rate 20.1%).
• Xia, W., Yang, Y., Xue, J.-H. and Feng, W. (2020) Controllable continuous gaze redirection. ACM International Conference on Multimedia (ACM MM, acceptance rate 27.9%), 1782-1790.
• Ruan, D., Yan, Y., Chen, S., Xue, J.-H. and Wang, H. (2020) Deep disturbance-disentangled learning for facial expression recognition. ACM International Conference on Multimedia (ACM MM, acceptance rate 27.9%), 2833-2841.
• Yang, X., Dong, M., Guo, Y. and Xue, J.-H. (2020) Metric learning for categorical and ambiguous features: An adversarial method. Joint European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD, acceptance rate 19%), 223-238.

Past Journal Publications

• Zhang, Z., Chang, D., Zhu, R., Li, X., Ma, Z. and Xue, J.-H. (2025) Query-aware cross-mixup and cross-reconstruction for few-shot fine-grained image classification. IEEE Transactions on Circuits and Systems for Video Technology, 35(2), 1276-1286.
• Li, X., Wang, X., Zhu, R., Ma, Z., Cao, J. and Xue, J.-H. (2025) Selectively augmented attention network for few-shot image classification. IEEE Transactions on Circuits and Systems for Video Technology, 35(2), 1180-1192.
• Xuan, F., Liu, H., Xue, J.-H., Li, Y., Huang, X., Tan, Z., Abd Elbasit, M.A.M., Gu, X. and Su, W. (2024) The novel triangular spectral indices for characterizing winter wheat drought. International Journal of Applied Earth Observation and Geoinformation, 134, 104151.
• Chien, J.-T., Chen, M.-Y., Lee, C.-H. and Xue, J.-H. (2024) Meta soft prompting and learning. APSIPA Transactions on Signal and Information Processing, 13(5), e402.
• Huang, G., Yan, Y., Xue, J.-H., Zhu, W. and Luo, X. (2024) Interpretable heterogeneous teacher-student learning framework for hybrid-supervised pulmonary nodule detection. IEEE Transactions on Circuits and Systems for Video Technology, 34(12), 12100-12111.
• Li, X., Guo, Z., Zhu, R., Ma, Z., Guo, J. and Xue, J.-H. (2024) A simple scheme to amplify inter-class discrepancy for improving few-shot fine-grained image classification. Pattern Recognition, 156, 110736.
• Zhang, X., Cheng, I., Jing, Y., Shi, J., Li, C., Xue, J.-H., Tam, L.-S. and Yu, W. (2024) DCES-PA: Deformation-controllable elastic shape model for 3D bone proliferation analysis using hand HR-pQCT images. Computers in Biology and Medicine, 175, 108533.
• Li, X., Li, Z., Xie, J., Yang, X., Xue, J.-H. and Ma, Z. (2024) Self-reconstruction network for fine-grained few-shot classification. Pattern Recognition, 153, 110485.
• Lv, Y., Huang, G., Yan, Y., Xue, J.-H., Chen, S. and Wang, H. (2024) Visual-textual attribute learning for class-incremental facial expression recognition. IEEE Transactions on Multimedia, 26, 8038-8051.
• Wu, W., Shao, Y., Gao, C., Xue, J.-H. and Sang, N. (2024) Query-centric distance modulator for few-shot classification. Pattern Recognition, 151, 110380.
• Myung, W., Su, N., Xue, J.-H. and Wang, G. (2024) DeGCN: Deformable graph convolutional networks for skeleton-based action recognition. IEEE Transactions on Image Processing, 33, 2477-2490.
• Lv, Y., Yan, Y., Xue, J.-H., Chen, S. and Wang, H. (2024) Relationship-guided knowledge transfer for class-incremental facial expression recognition. IEEE Transactions on Image Processing, 33, 2293-2304.
• Yang, F., Jiang, R., Yan, Y., Xue, J.-H., Wang, B. and Wang, H. (2024) Dual-mode learning for multi-dataset X-ray security image detection. IEEE Transactions on Information Forensics and Security, 19, 3510-3524.
• Xu, Y., Yan, Y., Xue, J.-H., Hua, Y. and Wang, H. (2024) Unpaired caricature-visual face recognition via feature decomposition-restoration-decomposition. IEEE Transactions on Circuits and Systems for Video Technology, 34(7), 5693-5703.
• Zhang, J., Liao, Q., Ma, H., Xue, J.-H., Yang, W. and Liu, S. (2024) Exploit the best of both end-to-end and map-based methods for multi-focus image fusion. IEEE Transactions on Multimedia, 26, 6411-6423.
• Zhao, P., Song, Y., Wang, S., Xue, J.-H., Zhao, S., Liao, Q. and Yang, W. (2024) VPCFormer: A transformer-based multi-view finger vein recognition model and a new benchmark. Pattern Recognition, 148, 110170.
• Jiang, R., Yan, Y., Xue, J.-H., Chen, S., Wang, N. and Wang, H. (2025) Knowledge distillation meets label noise learning: Ambiguity-guided mutual label refinery. IEEE Transactions on Neural Networks and Learning Systems, 36(1), 939-952.
• Xia, W. and Xue, J.-H. (2024) A survey on deep generative 3D-aware image synthesis. ACM Computing Surveys, 56(4), 90.
• Wan, J., Dong, Y., Yao, Y., Xiao, W., Huang, R., Xue, J.-H., Peng, R., Pei, H., Tian, X., Liao, R., He, H., Zeng, N., Li, C. and Ma, H. (2023) Unsupervised learning of pixel clustering in Mueller matrix images for mapping microstructural features in pathological tissues. Communications Engineering, 2, 88.
• An, S., Liao, Q., Lu, Z. and Xue, J.-H. (2024) Dual correlation network for efficient video semantic segmentation. IEEE Transactions on Circuits and Systems for Video Technology, 34(3), 1572-1585.
• Li, X., Song, Q., Wu, J., Zhu, R., Ma, Z. and Xue, J.-H. (2023) Locally-enriched cross-reconstruction for few-shot fine-grained image classification. IEEE Transactions on Circuits and Systems for Video Technology, 33(12), 7530-7540.
• Yan, Y., Shu, Y., Chen, S., Xue, J.-H., Shen, C. and Wang, H. (2023) SPL-Net: Spatial-semantic patch learning network for facial attribute recognition with limited labeled data. International Journal of Computer Vision, 131, 2097-2121.
• Sun, T., Zhang, G., Yang, W., Xue, J.-H. and Wang, G. (2023) TROSD: A new RGB-D dataset for transparent and reflective object segmentation in practice. IEEE Transactions on Circuits and Systems for Video Technology, 33(10), 5721-5733.
• Zhang, X., Cheng, I., Liu, S., Li, C., Xue, J.-H., Tam, L.-S. and Yu, W. (2023) Automatic 3D joint erosion detection for the diagnosis and monitoring of rheumatoid arthritis using hand HR-pQCT images. Computerized Medical Imaging and Graphics, 106, 102200.
• Zhu, R., Zhou, F., Yang, W. and Xue, J.-H. (2023) Statistical hypothesis testing as a novel perspective of pooling for image quality assessment. Signal Processing: Image Communication, 114, 116942.
• Li, X., Yang, X., Ma, Z. and Xue, J.-H. (2023) Deep metric learning for few-shot image classification: A review of recent developments. Pattern Recognition, 138, 109381.
• Zhao, P., Chen, Z., Xue, J.-H., Feng, J., Yang, W., Liao, Q. and Zhou, J. (2023) Single-sample finger vein recognition via competitive and progressive sparse representation. IEEE Transactions on Biometrics, Behavior, and Identity Science, 5(2), 209-220.
• Zhao, P., Zhao, S., Xue, J.-H., Yang, W. and Liao, Q. (2023) The neglected background cues can facilitate finger vein recognition. Pattern Recognition, 136, 109199.
• Li, X., Li, Y., Zheng, Y., Zhu, R., Ma, Z., Xue, J.-H. and Cao, J. (2023) ReNAP: Relation network with adaptive prototypical learning for few-shot classification. Neurocomputing, 520, 356-364.
• Yang, X., Guo, Y., Dong, M. and Xue, J.-H. (2024) Towards certified robustness of distance metric learning. IEEE Transactions on Neural Networks and Learning Systems, 35(3), 3834-3844.
• Ling, Y., Liu, Z. and Xue, J.-H. (2024) Survival analysis of high-dimensional data with graph convolutional networks and geometric graphs. IEEE Transactions on Neural Networks and Learning Systems, 35(4), 4876-4886.
• Jiang, R., Yan, Y., Xue, J.-H., Wang, B. and Wang, H. (2024) When sparse neural network meets label noise learning: A multi-stage learning framework. IEEE Transactions on Neural Networks and Learning Systems, 35(2), 2208-2222.
• Xia, W., Zhang, Y., Yang, Y., Xue, J.-H., Zhou, B. and Yang, M.-H. (2023) GAN inversion: A survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(3), 3121-3138.
• Chen, J., Gao, B.-B., Lu, Z., Xue, J.-H., Wang, C. and Liao, Q. (2023) APANet: Adaptive prototypes alignment network for few-shot semantic segmentation. IEEE Transactions on Multimedia, 25, 4361-4373.
• Yan, Y., Xu, Y., Xue, J.-H., Yang, L., Wang, H. and Zhu, W. (2023) Drop loss for person attribute recognition with imbalanced noisy-labeled samples. IEEE Transactions on Cybernetics, 53(11), 7071-7084.
• Fukui, K., Sogi, N., Kobayashi, T., Xue, J.-H. and Maki, A. (2023) Discriminant feature extraction by generalized difference subspace. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(2), 1618-1635.
• Mitchell, A., Erfanian, M., Soelistyo, C., Oberman, T., Kang, J., Aldridge, R., Xue, J.-H. and Aletta, F. (2022) Effects of soundscape complexity on urban noise annoyance ratings: A large-scale online listening experiment. International Journal of Environmental Research and Public Health, 19(22), 14872.
• Wan, J., Dong, Y., Xue, J.-H., Lin, L., Du, S., Dong, J., Yao, Y., Li, C. and Ma, H. (2022) Polarization-based probabilistic discriminative model for quantitative characterization of cancer cells. Biomedical Optics Express, 13(6), 3339-3354.
• Tao, W., Wang, X., Xue, J.-H., Su, W., Zhang, M., Yin, D., Zhu, D., Xie, Z. and Zhang, Y. (2022) Monitoring the damage of armyworm as a pest in summer corn by unmanned aerial vehicle imaging. Pest Management Science, 78(6), 2265-2276.
• Ling, Y., Zhou, F., Guo, K. and Xue, J.-H. (2022) ASSP: An adaptive sample statistics-based pooling for full-reference image quality assessment. Neurocomputing, 493, 568-582.
• Chen, S., Xue, J.-H., Chang, J., Zhang, J., Yang, J. and Tian, Q. (2022) SSL++: Improving self-supervised learning by mitigating the proxy task-specificity problem. IEEE Transactions on Image Processing, 31, 1134-1148.
• Ruan, D., Mo, R., Yan, Y., Chen, S., Xue, J.-H. and Wang, H. (2022) Adaptive deep disturbance-disentangled learning for facial expression recognition. International Journal of Computer Vision, 130, 455-477.
• An, S., Liao, Q., Lu, Z. and Xue, J.-H. (2022) Efficient semantic segmentation via self-attention and self-distillation. IEEE Transactions on Intelligent Transportation Systems, 23(9), 15256-15266.
• Ma, H., Liu, S., Liao, Q., Zhang, J. and Xue, J.-H. (2022) Defocus image deblurring network with defocus map estimation as auxiliary task. IEEE Transactions on Image Processing, 31, 216-226.
• Xie, J., Ma, Z., Xue, J.-H., Zhang, G., Sun, J., Zheng, Y. and Guo, J. (2021) DS-UI: Dual-supervised mixture of Gaussian mixture models for uncertainty inference in image recognition. IEEE Transactions on Image Processing, 30, 9208-9219.
• Weng, X., Yan, Y., Chen, S., Xue, J.-H. and Wang, H. (2022) Stage-aware feature alignment network for real-time semantic segmentation of street scenes. IEEE Transactions on Circuits and Systems for Video Technology, 32(7), 4444-4459.
• Dong, Y., Wan, J., Wang, X., Xue, J.-H., Zou, J., He, H., Li, P., Hou, A. and Ma, H. (2021) A polarization-imaging-based machine learning framework for quantitative pathological diagnosis of cervical precancerous lesions. IEEE Transactions on Medical Imaging, 40(12), 3728-3738.
• Xia, W., Yang, Y. and Xue, J.-H. (2021) Cali-Sketch: Stroke calibration and completion for high-quality face image generation from human-like sketches. Neurocomputing, 460, 256-265.
• Sogi, N., Zhu, R., Xue, J.-H. and Fukui, K. (2022) Constrained mutual convex cone method for image set based recognition. Pattern Recognition, 121, 108190.
• Xie, J., Ma, Z., Lei, J., Zhang, G., Xue, J.-H., Tan, Z.-H. and Guo, J. (2022) Advanced dropout: A model-free methodology for Bayesian dropout optimization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(9), 4605-4625.
• Han, X., Zhang, H., Xue, J.-H. and Sun, W. (2022) A spectral-spatial jointed spectral super-resolution and its application to HJ-1A satellite images. IEEE Geoscience and Remote Sensing Letters, 19, 5505905.
• Zhang, Y., Lu, Z., Zhang, X., Xue, J.-H. and Liao, Q. (2022) Deep learning in lane marking detection: A survey. IEEE Transactions on Intelligent Transportation Systems, 23(7), 5976-5992.
• Liu, L., Wang, B., Kuang, Z., Xue, J.-H., Chen, Y., Yang, W., Liao, Q. and Zhang, W. (2022) GenDet: Meta learning to generate detectors from few shots. IEEE Transactions on Neural Networks and Learning Systems, 33(8), 3448-3460.
• Li, X., Wu, J., Sun, Z., Ma, Z., Cao, J. and Xue, J.-H. (2021) BSNet: Bi-similarity network for few-shot fine-grained image classification. IEEE Transactions on Image Processing, 30, 1318-1331.
• Zhang, G., Xue, J.-H., Xie, P., Yang, S. and Wang, G. (2021) Non-local aggregation for RGB-D semantic segmentation. IEEE Signal Processing Letters, 28, 658-662.
• Li, X., Sun, Z., Xue, J.-H. and Ma, Z. (2021) A concise review of recent few-shot meta-learning methods. Neurocomputing, 456, 463-468.
• Li, X., Chang, D., Ma, Z., Tan, Z.-H., Xue, J.-H., Cao, J. and Guo, J. (2021) Deep InterBoost networks for small-sample image classification. Neurocomputing, 456, 492-503.
• Deng, G., Ming, Y. and Xue, J.-H. (2021) RFRN: A recurrent feature refinement network for accurate and efficient scene text detection. Neurocomputing, 453, 465-481.
• Ming, Y., Feng, F., Li, C. and Xue, J.-H. (2021) 3D-TDC: A 3D temporal dilation convolution framework for video action recognition. Neurocomputing, 450, 362-371.
• Liu, Y., Peng, J., Xue, J.-H., Chen, Y. and Fu, Z.-H. (2021) TSingNet: Scale-aware and context-rich feature learning for traffic sign detection and recognition in the wild. Neurocomputing, 447, 10-22.
• Li, Z., Ming, Y., Yang, L. and Xue, J.-H. (2021) Mutual-learning sequence-level knowledge distillation for automatic speech recognition. Neurocomputing, 428, 259-267.
• Lu, X., Qiao, Y., Zhu, R., Wang, G., Ma, Z. and Xue, J.-H. (2021) Generalisations of stochastic supervision models. Pattern Recognition, 109, 107575.
• Zhang, X., Yan, Y., Xue, J.-H., Hua, Y. and Wang, H. (2021) Semantic-aware occlusion-robust network for occluded person re-identification. IEEE Transactions on Circuits and Systems for Video Technology, 31(7), 2764-2778.
• Li, X., Yu, L., Yang, X., Ma, Z., Xue, J.-H., Cao, J. and Guo, J. (2021) ReMarNet: Conjoint relation and margin learning for small-sample image classification. IEEE Transactions on Circuits and Systems for Video Technology, 31(4), 1569-1579.
• Xia, W., Yang, Y., Xue, J.-H. and Xiao, J. (2021) Domain fingerprints for no-reference image quality assessment. IEEE Transactions on Circuits and Systems for Video Technology, 31(4), 1332-1341.
• Mao, L., Yan, Y., Xue, J.-H. and Wang, H. (2022) Deep multi-task multi-label CNN for effective facial attribute classification. IEEE Transactions on Affective Computing, 13(2), 818-828.
• Zhang, Y., Lu, Z., Ma, D., Xue, J.-H. and Liao, Q. (2021) Ripple-GAN: Lane line detection with ripple lane line detection network and Wasserstein GAN. IEEE Transactions on Intelligent Transportation Systems, 22(3), 1532-1542.
• Zhang, W., Chen, Y., Yang, W., Wang, G., Xue, J.-H. and Liao, Q. (2021) Class-variant margin normalized softmax loss for deep face recognition. IEEE Transactions on Neural Networks and Learning Systems, 32(10), 4742-4747.
• Ma, Z., Lu, X., Xie, J., Yang, Z., Xue, J.-H., Tan, Z.-H., Xiao, B. and Guo, J. (2023) On the comparisons of decorrelation approaches for non-Gaussian neutral vector variables. IEEE Transactions on Neural Networks and Learning Systems, 34(4), 1823-1837.
• Liu, L., Kuang, Z., Chen, Y., Xue, J.-H., Yang, W. and Zhang, W. (2021) IncDet: In defense of elastic weight consolidation for incremental object detection. IEEE Transactions on Neural Networks and Learning Systems, 32(6), 2306-2319.
• Liu, S., Liao, Q., Xue, J.-H. and Zhou, F. (2020) Defocus map estimation from a single image using improved likelihood feature and edge-based basis. Pattern Recognition, 107, 107485.
• Yang, X., Dong, M., Wang, Z., Gao, L., Zhang, L. and Xue, J.-H. (2020) Data-augmented matched subspace detector for hyperspectral subpixel target detection. Pattern Recognition, 106, 107464.
• Souza, L.S., Gatto, B.B., Xue, J.-H. and Fukui, K. (2020) Enhanced Grassmann discriminant analysis with randomized time warping for motion recognition. Pattern Recognition, 97, 107028.
• Zhang, J., Liao, Q., Liu, S., Ma, H., Yang, W. and Xue, J.-H. (2020) Real-MFF: A large realistic multi-focus image dataset with ground truth. Pattern Recognition Letters, 138, 370-377.
• Zhu, R., Guo, Y. and Xue, J.-H. (2020) Adjusting the imbalance ratio by the dimensionality of imbalanced data. Pattern Recognition Letters, 133, 217-223.
• Xia, W., Yang, Y. and Xue, J.-H. (2020) Unsupervised multi-domain multimodal image-to-image translation with explicit domain-constrained disentanglement. Neural Networks, 131, 50-63.
• Zhang, F., Yang, G. and Xue, J.-H. (2020) Hyperspectral image denoising based on low-rank coefficients and orthonormal dictionary. Signal Processing, 177, 107738.
• Sun, J., Yang, W., Gao, R., Xue, J.-H. and Liao, Q. (2020) Inter-class angular margin loss for face recognition. Signal Processing: Image Communication, 80, 115636.
• Ma, H., Liao, Q., Zhang, J., Liu, S. and Xue, J.-H. (2020) An α-matte boundary defocus model-based cascaded network for multi-focus image fusion. IEEE Transactions on Image Processing, 29, 8668-8679.
• Li, X., Chang, D., Ma, Z., Tan, Z.-H., Xue, J.-H., Cao, J., Yu, J. and Guo, J. (2020) OSLNet: Deep small-sample classification with an orthogonal softmax layer. IEEE Transactions on Image Processing, 29, 6482-6495.
• Han, X., Yu, J., Xue, J.-H. and Sun, W. (2020) Hyperspectral and multispectral image fusion using optimized twin dictionaries. IEEE Transactions on Image Processing, 29, 4709-4720.
• Yang, W., Zhang, X., Tian, Y., Wang, W., Xue, J.-H. and Liao, Q. (2020) LCSCNet: Linear compressing based skip-connecting network for image super-resolution. IEEE Transactions on Image Processing, 29, 1450-1464.
• Sun, J., Yang, W., Xue, J.-H. and Liao, Q. (2020) An equalized margin loss for face recognition. IEEE Transactions on Multimedia, 22(11), 2833-2843.
• Wang, G., Zhang, C., Chen, X., Ji, X., Xue, J.-H. and Wang, H. (2020) Bi-stream pose-guided region ensemble network for fingertip localization from stereo images. IEEE Transactions on Neural Networks and Learning Systems, 31(12), 5153-5165.
• Zhu, R., Wang, Z., Sogi, N., Fukui, K. and Xue, J.-H. (2020) A novel separating hyperplane classification framework to unify nearest-class-model methods for high-dimensional data. IEEE Transactions on Neural Networks and Learning Systems, 31(10), 3866-3876.
• Ma, Z., Xie, J., Lai, Y., Taghia, J., Xue, J.-H. and Guo, J. (2020) Insights into multiple/single lower bound approximation for extended variational inference in non-Gaussian structured data modeling. IEEE Transactions on Neural Networks and Learning Systems, 31(7), 2240-2254.
• Dong, M., Wang, Y., Yang, X. and Xue, J.-H. (2020) Learning local metrics and influential regions for classification. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(6), 1522-1529.
• Yang, W., Zhang, X., Tian, Y., Wang, W., Xue, J.-H. and Liao, Q. (2019) Deep learning for single image super-resolution: A brief review. IEEE Transactions on Multimedia, 21(12), 3106-3121.
• Zhu, R., Dong, M. and Xue, J.-H. (2019) Learning distance to subspace for the nearest subspace methods in high-dimensional data classification. Information Sciences, 481, 69-80.
• Yang, X., Zhang, L., Gao, L. and Xue, J.-H. (2019) MSDH: Matched subspace detector with heterogeneous noise. Pattern Recognition Letters, 125, 701-707.
• Zhang, M., Su, W., Fu, Y., Zhu, D., Xue, J.-H., Huang, J., Wang, W., Wu, J. and Yao, C. (2019) Super-resolution enhancement of Sentinel-2 image for retrieving LAI and chlorophyll content of summer corn. European Journal of Agronomy, 111, 125938.
• Huang, J., Gomez-Dans, J.L., Huang, H., Ma, H., Wu, Q., Lewis, P.E., Liang, S., Chen, Z., Xue, J.-H., Wu, Y., Zhao, F., Wang, J. and Xie, X. (2019) Assimilation of remote sensing into crop growth models: Current status and perspectives. Agricultural and Forest Meteorology, 276-277, 107609.
• Yang, W., Hui, C., Chen, Z., Xue, J.-H. and Liao, Q. (2019) FV-GAN: Finger vein representation using generative adversarial networks. IEEE Transactions on Information Forensics and Security, 14(9), 2512-2524.
• Zhu, F., Ma, Z., Li, X., Chen, G., Chien, J.-T., Xue, J.-H. and Guo, J. (2019) Image-text dual neural network with decision strategy for small-sample image classification. Neurocomputing, 328, 182-188.
• Yang, W., Ji, W., Xue, J.-H., Ren, Y. and Liao, Q. (2019) A hybrid finger identification pattern using polarized depth-weighted binary direction coding. Neurocomputing, 325, 260-268.
• Zhu, R., Wang, Z., Ma, Z., Wang, G. and Xue, J.-H. (2018) LRID: A new metric of multi-class imbalance degree based on likelihood-ratio test. Pattern Recognition Letters, 116, 36-42.
• Wang, Z., Zhu, R., Fukui, K. and Xue, J.-H. (2018) Cone-based joint sparse modelling for hyperspectral image classification. Signal Processing, 144, 417-429.
• Zhu, R., Zhou, F., Yang, W. and Xue, J.-H. (2018) On hypothesis testing for comparing image quality assessment metrics [Tips & Tricks]. IEEE Signal Processing Magazine, 35(4), 133-136.
• Sun, W., Liao, Q., Xue, J.-H. and Zhou, F. (2018) SPSIM: A superpixel-based similarity index for full-reference image quality assessment. IEEE Transactions on Image Processing, 27(9), 4232-4244.
• Ma, Z., Xue, J.-H., Leijon, A., Tan, Z.-H., Yang, Z. and Guo, J. (2018) Decorrelation of neutral vector variables: Theory and applications. IEEE Transactions on Neural Networks and Learning Systems, 29(1), 129-143.
• Zeng, Z., Yang, W., Sun, W., Xue, J.-H. and Liao, Q. (2018) No-reference image quality assessment for photographic images based on robust statistics. Neurocomputing, 313, 111-118.
• Wang, Z., Hu, H., Zhang, L. and Xue, J.-H. (2018) Discriminatively guided filtering (DGF) for hyperspectral image classification. Neurocomputing, 275, 1981-1987.
• Zhu, R., Zhou, F. and Xue, J.-H. (2018) MvSSIM: A quality assessment index for hyperspectral images. Neurocomputing, 272, 250-257.
• Wang, Z. and Xue, J.-H. (2018) Matched shrunken subspace detectors for hyperspectral target detection. Neurocomputing, 272, 226-236.
• Wang, Z., Zhu, R., Fukui, K. and Xue, J.-H. (2017) Matched shrunken cone detector (MSCD): Bayesian derivations and case studies for hyperspectral target detection. IEEE Transactions on Image Processing, 26(11), 5447-5461.
• Lapuyade-Lahorgue, J., Xue, J.-H. and Ruan, S. (2017) Segmenting multi-source images using hidden Markov fields with copula-based multivariate statistical distributions. IEEE Transactions on Image Processing, 26(7), 3187-3195.
• Zhu, R. and Xue, J.-H. (2017) On the orthogonal distance to class subspaces for high-dimensional data classification. Information Sciences, 417, 262-273.
• Zhu, R., Fukui, K. and Xue, J.-H. (2017) Building a discriminatively ordered subspace on the generating matrix to classify high-dimensional spectral data. Information Sciences, 382-383, 1-14.
• Wang, Z. and Xue, J.-H. (2017) The matched subspace detector with interaction effects. Pattern Recognition, 68, 24-37.
• Wang, Z., Liu, J. and Xue, J.-H. (2017) Joint sparse model-based discriminative K-SVD for hyperspectral image classification. Signal Processing, 133, 144-155.
• Jiang, W., Xue, J.-H. and Yu, W. (2017) What is the probability of replicating a statistically significant association in genome-wide association studies? Briefings in Bioinformatics, 18(6), 928-939.
• Suryanto, C.H., Xue, J.-H. and Fukui, K. (2016) Randomized time warping for motion recognition. Image and Vision Computing, 54, 1-11.
• Guo, Y., Ding, X., Liu, C. and Xue, J.-H. (2016) Sufficient canonical correlation analysis. IEEE Transactions on Image Processing, 25(6), 2610-2619.
• Wang, M., Yu, J., Xue, J.-H. and Sun, W. (2016) Denoising of hyperspectral images using group low-rank representation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(9), 4420-4427.
• Chen, H., Wang, G., Xue, J.-H. and He, L. (2016) A novel hierarchical framework for human action recognition. Pattern Recognition, 55, 148-159.
• He, L., Wang, G., Liao, Q. and Xue, J.-H. (2016) Latent variable pictorial structure for human pose estimation on depth images. Neurocomputing, 203, 52-61.
• Liang, Y., Ding, X., Liu, C. and Xue, J.-H. (2016) Combining multiple biometric traits with an order-preserving score fusion algorithm. Neurocomputing, 171, 252-261.
• Xue, J.-H. and Hall, P. (2015) Why does rebalancing class-unbalanced data improve AUC for linear discriminant analysis? IEEE Transactions on Pattern Analysis and Machine Intelligence, 37(5), 1109-1112.
• Liang, Y., Ding, X. and Xue, J.-H. (2015) Advanced joint Bayesian method for face verification. IEEE Transactions on Information Forensics and Security, 10(2), 346-354.
• Zhu, R., Dong, M. and Xue, J.-H. (2015) Spectral non-local restoration of hyperspectral images with low-rank property. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(6), 3062-3067.
• He, L., Wang, G., Liao, Q. and Xue, J.-H. (2015) Depth-images-based pose estimation using regression forests and graphical models. Neurocomputing, 164, 210-219.
• Guo, Y., Ding, X. and Xue, J.-H. (2015) MiLDA: A graph embedding approach to multi-view face recognition. Neurocomputing, 151(3), 1255-1261.
• Wang, G., Zheng, F., Shi, C., Xue, J.-H., Liu, C. and He, L. (2015) Embedding metric learning into set-based face recognition for video surveillance. Neurocomputing, 151(3), 1500-1506.
• Ruan, Z., Wang, G., Xue, J.-H. and Lin, X. (2015) Subcategory clustering with latent feature alignment and filtering for object detection. IEEE Signal Processing Letters, 22(2), 244-248.
• Guo, Y., Ding, X., Fang, C. and Xue, J.-H. (2014) Fisher's linear discriminant embedded metric learning. Neurocomputing, 143, 7-13.
• Ruan, Z., Wang, G., Xue, J.-H., Lin, X. and Jiang, Y. (2014) Detection of user-registered dog faces. Neurocomputing, 142, 256-266.
• Ruan, Z., Wang, G., Lin, X., Xue, J.-H. and Jiang, Y. (2014) Deformable part-based model transfer for object detection. IEICE Transactions on Information and Systems, E97-D(5), 1394-1397.
• Hall, P. and Xue, J.-H. (2014) On selecting interacting features from high-dimensional data. Computational Statistics & Data Analysis, 71, 694-708.
• Hall, P., Xia, Y. and Xue, J.-H. (2013) Simple tiered classifiers. Biometrika, 100(2), 431-445.
• Xue, J.-H. and Zhang, Y.-J. (2012) Ridler and Calvard's, Kittler and Illingworth's and Otsu's methods for image thresholding. Pattern Recognition Letters, 33(6), 793-797.
• Xue, J.-H. and Titterington, D.M. (2011) Median-based image thresholding. Image and Vision Computing, 29(9), 631-637.
• Xue, J.-H. and Titterington, D.M. (2011) t-tests, F-tests and Otsu's methods for image thresholding. IEEE Transactions on Image Processing, 20(8), 2392-2396.
• Xue, J.-H. and Titterington, D.M. (2011) The p-folded cumulative distribution function and the mean absolute deviation from the p-quantile. Statistics & Probability Letters, 81(8), 1179-1182.
• Xue, J.-H. and Titterington, D.M. (2010) Joint discriminative-generative modelling based on statistical tests for classification. Pattern Recognition Letters, 31(9), 1048-1055.
• Hall, P. and Xue, J.-H. (2010) Incorporating prior probabilities into high-dimensional classifiers. Biometrika, 97(1), 31-48.
• Xue, J.-H. and Titterington, D.M. (2010) On the generative-discriminative tradeoff approach: Interpretation, asymptotic efficiency and classification performance. Computational Statistics & Data Analysis, 54(2), 438-451.
• Hall, P., Titterington, D.M. and Xue, J.-H. (2009) Median-based classifiers for high-dimensional data. Journal of the American Statistical Association, 104(488), 1597-1608.
• Hall, P., Titterington, D.M. and Xue, J.-H. (2009) Tilting methods for assessing the influence of components in a classifier. Journal of the Royal Statistical Society: Series B, 71(4), 783-803.
• Xue, J.-H. and Titterington, D.M. (2009) Interpretation of hybrid generative/discriminative algorithms. Neurocomputing, 72(7-9), 1648-1655.
• Xue, J.-H. and Titterington, D.M. (2008) Comment on "On discriminative vs. generative classifiers: a comparison of logistic regression and naive Bayes." Neural Processing Letters, 28(3), 169-187.
• Xue, J.-H. and Titterington, D.M. (2008) Short note on two output-dependent hidden Markov models. Pattern Recognition Letters, 29(9), 1424-1426.
• Xue, J.-H. and Titterington, D.M. (2008) Do unbalanced data have a negative effect on LDA? Pattern Recognition, 41(5), 1558-1571.
• Short Discussions
  • Zhu, R., Yang, X., Ling, Y. and Xue, J.-H. (2017) Discussion of "A Bayesian information criterion for singular models" by Drton, M. and Plummer, M. Journal of the Royal Statistical Society: Series B, 79(2), 374.
  • Ling, Y., Yang, X. and Xue, J.-H. (2017) Discussion of "Random-projection ensemble classification" by Cannings, T.I. and Samworth, R.J. Journal of the Royal Statistical Society: Series B, 79(4), 1015-1016.
  • Lu, X. and Xue, J.-H. (2017) Discussion of "Random-projection ensemble classification" by Cannings, T.I. and Samworth, R.J. Journal of the Royal Statistical Society: Series B, 79(4), 1019.
  • Xue, J.-H. and Titterington, D.M. (2010) Discussion of "Maximum likelihood estimation of a multi-dimensional log-concave density" by Cule, M.L., Samworth, R.J. and Stewart, M.I. Journal of the Royal Statistical Society: Series B, 72(5), 582.
  • Hall, P., Titterington, D.M. and Xue, J.-H. (2008) Discussion of "Sure independence screening for ultrahigh dimensional feature space" by Fan, J. and Lv, J. Journal of the Royal Statistical Society: Series B, 70(5), 889-890.