Staff profile

Yang Long is an Associate Professor in the Department of Computer Science, Durham University. He is also an IEEE Senior Member (SMIEEE) and 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 100+ top-tier papers in refereed journals/conferences such as IEEE TPAMI, TIP, CVPR, AAAI, and ACM MM.

Conference Paper

• Aduragba, T. O., Yu, J., Cristea, A. I., & Long, Y. (2023, December). Improving Health Mention Classification through Emphasising Literal Meanings: a Study Towards Diversity and Generalisation for Public Health Surveillance. Presented at TheWebConf2023, Austin, Texas
• Li, Y., Wan, F., & Long, Y. (2024, July). SID-NERF: Few-Shot Nerf Based on Scene Information Distribution. Presented at 2024 IEEE International Conference on Multimedia and Expo (ICME), Niagara Falls, ON, Canada
• Mao, H., Zhang, H., Long, Y., Wang, S., & Yang, L. (2019, December). A General Transductive Regularizer for Zero-Shot Learning. Presented at BMVC
• Wang, J., Hu, B., Long, Y., & Guan, Y. (2019, December). Order Matters: Shuffling Sequence Generation for Video Prediction. Presented at BMVC
• Huang, Y., Long, Y., & Wang, L. (2019, December). Few-Shot Image and Sentence Matching via Gated Visual-Semantic Embedding. Presented at Thirty-Second AAAI Conference on Artificial Intelligence
• Long, Y., Liu, L., Shen, Y., & Shao, L. (2018, December). Towards affordable semantic searching: Zero-shot retrieval via dominant attributes. Presented at Thirty-Second AAAI Conference on Artificial Intelligence
• Guan, C., Qin, S., Ling, W., & Long, Y. (2018, December). Enhancing apparel data based on fashion theory for developing a novel apparel style recommendation system. Presented at World Conference on Information Systems and Technologies Springer, Cham
• Long, Y., Tan, Y., Organisciak, D., Yang, L., & Shao, L. (2018, December). Towards light-weight annotations: Fuzzy interpolative reasoning for zero-shot image classification. Presented at BMVC
• Cai, Z., Long, Y., & Shao, L. (2018, December). Adaptive Visual-Depth Fusion Transfer. Presented at ACCV
• Zhu, Y., Long, Y., Guan, Y., Newsam, S., & Shao, L. (2018, December). Towards Universal Representation for Unseen Action Recognition. Presented at 2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) IEEE; CVF; IEEE Comp Soc, 345 E 47TH ST, NEW YORK, NY 10017 USA
• Long, Y., Liu, L., Shao, L., Shen, F., Ding, G., & Han, J. (2017, December). From Zero-shot Learning to Conventional Supervised Classification: Unseen Visual Data Synthesis. Presented at Computer Vision and Pattern Recognition IEEE
• Long, Y., Liu, L., & Shao, L. (2017, December). Towards fine-grained open zero-shot learning: Inferring unseen visual features from attributes. Presented at 2017 IEEE Winter Conference on Applications of Computer Vision (WACV) IEEE
• Long, Y., & Shao, L. (2017, December). Learning to recognise unseen classes by a few similes. Presented at Proceedings of the 25th ACM international conference on Multimedia ACM
• Long, Y., & Shao, L. (2017, December). Describing unseen classes by exemplars: Zero-shot learning using grouped simile ensemble. Presented at 2017 IEEE winter conference on applications of computer vision (WACV) IEEE
• Long, Y., Liu, L., & Shao, L. (2016, December). Attribute embedding with visual-semantic ambiguity removal for zero-shot learning. Presented at BMVC

Doctoral Thesis

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

Journal Article

• Zhang, H., Long, Y., & Shao, L. (online). Zero-shot leaning and hashing with binary visual similes. Multimedia Tools and Applications, 1-19
• Jiang, C., Wang, S., Long, Y., Li, Z., Zhang, H., & Shao, L. (online). Imaginary-Connected Embedding in Complex Space for Unseen Attribute-Object Discrimination. IEEE Transactions on Pattern Analysis and Machine Intelligence, https://doi.org/10.1109/tpami.2024.3487631
• Miao, X., Bai, Y., Duan, H., Wan, F., Huang, Y., Long, Y., & Zheng, Y. (2024). CTNeRF: Cross-time Transformer for dynamic neural radiance field from monocular video. Pattern Recognition, 156, Article 110729. https://doi.org/10.1016/j.patcog.2024.110729
• Pu, J., Duan, H., Zhao, J., & Long, Y. (2024). Rules for Expectation: Learning to Generate Rules via Social Environment Modeling. IEEE Transactions on Circuits and Systems for Video Technology, 34(8), 6874-6887. https://doi.org/10.1109/tcsvt.2023.3334526
• Liu, X., Wang, C., Yang, G., Wang, C., Long, Y., Liu, J., & Zhang, Z. (2024). Leveraging Self-Distillation and Disentanglement Network to Enhance Visual–Semantic Feature Consistency in Generalized Zero-Shot Learning. Electronics, 13(10), Article 1977. https://doi.org/10.3390/electronics13101977
• Ma, T., Organisciak, D., Ma, W., & Long, Y. (2024). Towards Cognition-Aligned Visual Language Models via Zero-Shot Instance Retrieval. Electronics, 13(9), Article 1660. https://doi.org/10.3390/electronics13091660
• Duan, H., Wang, S., Ojha, V., Wang, S., Huang, Y., Long, Y., …Zheng, Y. (2024). Wearable-based behaviour interpolation for semi-supervised human activity recognition. Information Sciences, 665, Article 120393. https://doi.org/10.1016/j.ins.2024.120393
• Miao, X., Bai, Y., Duan, H., Huang, Y., Wan, F., Xu, X., Long, Y., & Zheng, Y. (2024). DS-Depth: Dynamic and Static Depth Estimation via a Fusion Cost Volume. IEEE Transactions on Circuits and Systems for Video Technology, 34(4), 2564-2576. https://doi.org/10.1109/tcsvt.2023.3305776
• Yang, F., Li, X., Duan, H., Xu, F., Huang, Y., Zhang, X., Long, Y., & 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
• Li, T., Wen, Z., Long, Y., Hong, Z., Zheng, S., Yu, L., Chen, B., Yang, X., & 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
• 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
• 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
• 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, 26, 3976 - 3986. 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
• 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., 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
• 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., & 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
• 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
• 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., & 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,
• 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