Staff profile

Yang Long is an Assistant Professor in the Department of Computer Science, Durham University. He is also an MRC Innovation Fellow aiming to design scalable AI solutions for large-scale healthcare applications. His research background is in the highly interdisciplinary field of Computer Vision and Machine Learning. While he is passionate about unveiling the black-box of AI brain and transferring the knowledge to seek Scalable, Interactable, Interpretable, and sustainable solutions for other disciplinary researches, e.g. physical activity, mental health, design, education, security, and geoengineering. He has authored/co-authored 20+ top-tier papers in refereed journals/conferences such as IEEE TPAMI, TIP, CVPR, AAAI, and ACM MM, and holds a patent and a Chinese National Grant.

Conference Paper

• Aduragba, T. O., Yu, J., Cristea, A. I., & Long, Y. (in press). Improving Health Mention Classification through Emphasising Literal Meanings: a Study Towards Diversity and Generalisation for Public Health Surveillance.
• Huang, Y., Long, Y., & Wang, L. (2019). Few-Shot Image and Sentence Matching via Gated Visual-Semantic Embedding. In Thirty-Second AAAI Conference on Artificial Intelligence ; proceedings (5342-5349)
• Mao, H., Zhang, H., Long, Y., Wang, S., & Yang, L. (2019). A General Transductive Regularizer for Zero-Shot Learning.
• Wang, J., Hu, B., Long, Y., & Guan, Y. (2019). Order Matters: Shuffling Sequence Generation for Video Prediction.
• Long, Y., Tan, Y., Organisciak, D., Yang, L., & Shao, L. (2018). Towards light-weight annotations: Fuzzy interpolative reasoning for zero-shot image classification.
• Long, Y., Liu, L., Shen, Y., & Shao, L. (2018). Towards affordable semantic searching: Zero-shot retrieval via dominant attributes. In Thirty-Second AAAI Conference on Artificial Intelligence ; proceedings (7210-7217)
• Guan, C., Qin, S., Ling, W., & Long, Y. (2018). Enhancing apparel data based on fashion theory for developing a novel apparel style recommendation system.
• Cai, Z., Long, Y., & Shao, L. (2018). Adaptive Visual-Depth Fusion Transfer.
• Zhu, Y., Long, Y., Guan, Y., Newsam, S., & Shao, L. (2018). Towards Universal Representation for Unseen Action Recognition. . https://doi.org/10.1109/cvpr.2018.00983
• Long, Y., & Shao, L. (2017). Learning to recognise unseen classes by a few similes.
• Long, Y., & Shao, L. (2017). Describing unseen classes by exemplars: Zero-shot learning using grouped simile ensemble.
• Long, Y., Liu, L., & Shao, L. (2017). Towards fine-grained open zero-shot learning: Inferring unseen visual features from attributes.
• Long, Y., Liu, L., Shao, L., Shen, F., Ding, G., & Han, J. (2017). From Zero-shot Learning to Conventional Supervised Classification: Unseen Visual Data Synthesis.
• Long, Y., Liu, L., & Shao, L. (2016). Attribute embedding with visual-semantic ambiguity removal for zero-shot learning.

Doctoral Thesis

• Long, Y. (2017). Zero-shot Image Classification. (Thesis). University of Sheffield. Retrieved from https://durham-repository.worktribe.com/output/1642055

Journal Article

• Yang, F., Li, X., Duan, H., Xu, F., Huang, Y., Zhang, X., …Zheng, Y. (2024). MRL-Seg: Overcoming Imbalance in Medical Image Segmentation With Multi-Step Reinforcement Learning. IEEE Journal of Biomedical and Health Informatics, 28(2), 858-869. https://doi.org/10.1109/jbhi.2023.3336726
• Duan, H., Long, Y., Wang, S., Zhang, H., Willcocks, C. G., & Shao, L. (2023). Dynamic Unary Convolution in Transformers. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(11), 12747 - 12759. https://doi.org/10.1109/tpami.2022.3233482
• Pang, S., He, X., Hao, W., & Long, Y. (2023). Feature fine-tuning and attribute representation transformation for zero-shot learning. Computer Vision and Image Understanding, 236, Article 103811. https://doi.org/10.1016/j.cviu.2023.103811
• Li, T., Wen, Z., Long, Y., Hong, Z., Zheng, S., Yu, L., …Shao, L. (2023). The Importance of Expert Knowledge for Automatic Modulation Open Set Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(11), 13730-13748. https://doi.org/10.1109/tpami.2023.3294505
• Miao, X., Bai, Y., Duan, H., Huang, Y., Wan, F., Xu, X., …Zheng, Y. (2023). DS-Depth: Dynamic and Static Depth Estimation via a Fusion Cost Volume. IEEE Transactions on Circuits and Systems for Video Technology, https://doi.org/10.1109/tcsvt.2023.3305776
• Wang, J., Jiang, Y., Long, Y., Sun, X., Pagnucco, M., & Song, Y. (2023). Deconfounding Causal Inference for Zero-shot Action Recognition. IEEE Transactions on Multimedia, https://doi.org/10.1109/tmm.2023.3318300
• Wang, R., Wei, Z., Duan, H., Ji, S., Long, Y., & Hong, Z. (2022). EfficientTDNN: Efficient Architecture Search for Speaker Recognition. IEEE/ACM Transactions on Audio, Speech and Language Processing, 30, 2267-2279. https://doi.org/10.1109/taslp.2022.3182856
• Zarei, M. R., Taheri, M., & Long, Y. (2021). Kernelized distance learning for zero-shot recognition. Information Sciences, 580, 801-818. https://doi.org/10.1016/j.ins.2021.09.032
• Bond-Taylor, S., Leach, A., Long, Y., & Willcocks, C. G. (2021). Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(11), 7327-7347. https://doi.org/10.1109/tpami.2021.3116668
• Zhang, H., Bai, H., Long, Y., Liu, L., & Shao, L. (2021). A plug-in attribute correction module for generalized zero-shot learning. Pattern Recognition, 112, Article 107767. https://doi.org/10.1016/j.patcog.2020.107767
• Zhang, H., Wang, Y., Long, Y., Yang, L., & Shao, L. (2021). Modality independent adversarial network for generalized zero shot image classification. Neural Networks, 134, 11-22. https://doi.org/10.1016/j.neunet.2020.11.007
• Zhang, H., Liu, L., Long, Y., Zhang, Z., & Shao, L. (2020). Deep transductive network for generalized zero shot learning. Pattern Recognition, 105, Article 107370. https://doi.org/10.1016/j.patcog.2020.107370
• Zhang, H., Liu, J., Yao, Y., & Long, Y. (2020). Pseudo Distribution on Unseen Classes for Generalized Zero Shot Learning. Pattern Recognition Letters, 135, 451-458. https://doi.org/10.1016/j.patrec.2020.05.021
• Zhang, H., Mao, H., Long, Y., Yang, W., & Shao, L. (2020). A Probabilistic Zero-Shot Learning Method via Latent Nonnegative Prototype Synthesis of Unseen Classes. IEEE Transactions on Neural Networks and Learning Systems, 31(7), 2361-2375. https://doi.org/10.1109/tnnls.2019.2955157
• Angelini, F., Fu, Z., Long, Y., Shao, L., & Naqvi, S. M. (2020). 2D Pose-Based Real-Time Human Action Recognition With Occlusion-Handling. IEEE Transactions on Multimedia, 22(6), 1433-1446. https://doi.org/10.1109/tmm.2019.2944745
• Wang, Y., Zhang, H., Zhang, Z., Long, Y., & Shao, L. (2020). Learning discriminative domain-invariant prototypes for generalized zero shot learning. Knowledge-Based Systems, 196, Article 105796. https://doi.org/10.1016/j.knosys.2020.105796
• Wang, Y., Zhang, H., Wang, S., Long, Y., & Yang, L. (2020). Semantic combined network for zero-shot scene parsing. IET Image Processing, 14(4), 757 -765. https://doi.org/10.1049/iet-ipr.2019.0870
• Li, J., Lan, X., Long, Y., Liu, Y., Chen, X., Shao, L., & Zheng, N. (2020). A Joint Label Space for Generalized Zero-Shot Classification. IEEE Transactions on Image Processing, 29, 5817-5831. https://doi.org/10.1109/tip.2020.2986892
• Zhou, L., Zhang, H., Long, Y., Shao, L., & Yang, J. (2019). Depth Embedded Recurrent Predictive Parsing Network for Video Scenes. IEEE Transactions on Intelligent Transportation Systems, 20(12), 4643-4654. https://doi.org/10.1109/tits.2019.2909053
• Gao, Y., Long, Y., Guan, Y., Basu, A., Baggaley, J., & Ploetz, T. (2019). Towards Reliable, Automated General Movement Assessment for Perinatal Stroke Screening in Infants Using Wearable Accelerometers. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 3(1), Article 12. https://doi.org/10.1145/3314399
• Zhang, H., Long, Y., & Shao, L. (2019). Zero-shot Hashing with orthogonal projection for image retrieval. Pattern Recognition Letters, 117, 201-209. https://doi.org/10.1016/j.patrec.2018.04.011
• Zhang, H., Long, Y., Liu, L., & Shao, L. (2019). Adversarial unseen visual feature synthesis for Zero-shot Learning. Neurocomputing, 329, 12-20. https://doi.org/10.1016/j.neucom.2018.10.043
• Zhang, H., Long, Y., Guan, Y., & Shao, L. (2019). Triple Verification Network for Generalized Zero-Shot Learning. IEEE Transactions on Image Processing, 28(1), 506-517. https://doi.org/10.1109/tip.2018.2869696
• Long, Y., Guan, Y., & Shao, L. (2019). Generic compact representation through visual-semantic ambiguity removal. Pattern Recognition Letters, 117, 186-192. https://doi.org/10.1016/j.patrec.2018.04.024
• Guan, C., Qin, S., & Long, Y. (2019). Apparel-based deep learning system design for apparel style recommendation. International Journal of Clothing Science and Technology, 31(3), 376-389. https://doi.org/10.1108/ijcst-02-2018-0019
• Zhang, H., Long, Y., Yang, W., & Shao, L. (2019). Dual-verification network for zero-shot learning. Information Sciences, 470, 43-57. https://doi.org/10.1016/j.ins.2018.08.048
• Zhang, H., Long, Y., & Zhao, C. (2018). Attribute relaxation from class level to instance level for zero-shot learning. Electronics Letters, 54(20), 1170-1172. https://doi.org/10.1049/el.2018.5027
• Long, Y., Liu, L., Shen, F., Shao, L., & Li, X. (2018). Zero-Shot Learning Using Synthesised Unseen Visual Data with Diffusion Regularisation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(10), 2498-2512. https://doi.org/10.1109/tpami.2017.2762295
• Cai, Z., Long, Y., & Shao, L. (2018). Adaptive RGB Image Recognition by Visual-Depth Embedding. IEEE Transactions on Image Processing, 27(5), 2471-2483. https://doi.org/10.1109/tip.2018.2806839
• Zhang, H., Liu, L., Long, Y., & Shao, L. (2018). Unsupervised Deep Hashing With Pseudo Labels for Scalable Image Retrieval. IEEE Transactions on Image Processing, 27(4), 1626-1638. https://doi.org/10.1109/tip.2017.2781422
• Long, Y., Zhu, F., Shao, L., & Han, J. (2018). Face recognition with a small occluded training set using spatial and statistical pooling. Information Sciences, 430, 634-644. https://doi.org/10.1016/j.ins.2017.10.042
• Long, Y., Guan, Y., & Shao, L. (2018). Generic compact representation through visual-semantic ambiguity removal. Pattern Recognition Letters, 186,
• Zhang, H., Long, Y., & Shao, L. (2018). Zero-shot leaning and hashing with binary visual similes. Multimedia Tools and Applications, 1-19
• Long, Y., Zhu, F., & Shao, L. (2016). Recognising occluded multi-view actions using local nearest neighbour embedding. Computer Vision and Image Understanding, 144, 36-45