Dr Yang Long, PhD
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.
Department of Computer Science
- 1: Long, Yang, Liu, Li, Shen, Fumin, Shao, Ling & Li, Xuelong (2018). Zero-Shot Learning Using Synthesised Unseen Visual Data with Diffusion Regularisation. EEE Transactions on Pattern Analysis and Machine Intelligence 40(10): 2498-2512.
- 2: Gao, Yan, Long, Yang, Guan, Yu, Basu, Anna, Baggaley, Jessica & Ploetz, Thomas (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): 12.
- 3: Zhou, Lingli, Zhang, Haofeng, Long, Yang, Shao, Ling & Yang, Jingyu (2019). Depth Embedded Recurrent Predictive Parsing Network for Video Scenes. IEEE Transactions on Intelligent Transportation Systems 1.
- 4: Huang, Yan, Long, Yang & Wang, Liang (2019), Few-Shot Image and Sentence Matching via Gated Visual-Semantic Embedding, AAAI.
- 5: Zhang, Haofeng, Long, Yang, Guan, Yu & Shao, Ling (2019). Triple Verification Network for Generalized Zero-Shot Learning. IEEE Transactions on Image Processing 28(1): 506-517.
- 6: Cai, Ziyun, Long, Yang & Shao, Ling (2018). Adaptive RGB Image Recognition by Visual-Depth Embedding. IEEE Transactions on Image Processing 27(5): 2471-2483.
- 7: Long, Yang, Liu, Li, Shen, Yuming & Shao, Ling (2018), Towards affordable semantic searching: Zero-shot retrieval via dominant attributes, Thirty-Second AAAI Conference on Artificial Intelligence. Thirty-Second AAAI Conference on Artificial Intelligence, 7210-7217.
- Mao, Huaqi, Zhang, Haofeng, Long, Yang, Wang, Shidong & Yang, Longzhi (2019), A General Transductive Regularizer for Zero-Shot Learning, BMVC.
- Wang, Junyan, Hu, Bingzhang, Long, Yang & Guan, Yu (2019), Order Matters: Shuffling Sequence Generation for Video Prediction, BMVC.
- Cai, Ziyuni, Long, Yang & Shao, Ling (2018), Adaptive Visual-Depth Fusion Transfer, ACCV.
- Guan, Congying, Qin, Shengfeng, Ling, Wessie & Long, Yang (2018), Enhancing apparel data based on fashion theory for developing a novel apparel style recommendation system, World Conference on Information Systems and Technologies Springer, Cham. 31-40.
- Long, Yang, Tan, Yao, Organisciak, Daniel, Yang, Longzhi & Shao, Ling (2018), Towards light-weight annotations: Fuzzy interpolative reasoning for zero-shot image classification, BMVC.
- Zhu, Yi, Long, Yang, Guan, Yu, Newsam, Shawn & Shao, Ling (2018), Towards Universal Representation for Unseen Action Recognition, IEEE Conference on Computer Vision and Pattern Recognition 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, IEEE, 9436-9445.
- Long, Yang & Shao, Ling (2017), Describing unseen classes by exemplars: Zero-shot learning using grouped simile ensemble, 2017 IEEE winter conference on applications of computer vision (WACV) IEEE. 907-915.
- Long, Yang, Liu, Li, Shao, Ling, Shen, Fumin, Ding, Guiguang & Han, Jungong (2017), From Zero-shot Learning to Conventional Supervised Classification: Unseen Visual Data Synthesis, Computer Vision and Pattern Recognition IEEE.
- Long, Yang & Shao, Ling (2017), Learning to recognise unseen classes by a few similes, Proceedings of the 25th ACM international conference on Multimedia ACM. 636-644.
- Long, Yang, Liu, Li & Shao, Ling (2017), Towards fine-grained open zero-shot learning: Inferring unseen visual features from attributes, 2017 IEEE Winter Conference on Applications of Computer Vision (WACV) IEEE. 944-952.
- Long, Yang, Liu, Li & Shao, Ling (2016), Attribute embedding with visual-semantic ambiguity removal for zero-shot learning, BMVC.
- Long, Yang (2017). Zero-shot Image Classification. University of Sheffield. PhD.
- Zhang, Haofeng, Long, Yang, Liu, Li & Shao, Ling (2019). Adversarial unseen visual feature synthesis for Zero-shot Learning. NEUROCOMPUTING 329: 12-20.
- Guan, Congying, Qin, Shengfeng & Long, Yang (2019). Apparel-based deep learning system design for apparel style recommendation. INTERNATIONAL JOURNAL OF CLOTHING SCIENCE AND TECHNOLOGY 31(3): 376-389.
- Zhang, Haofeng, Long, Yang, Yang, Wankou & Shao, Ling (2019). Dual-verification network for zero-shot learning. INFORMATION SCIENCES 470: 43-57.
- Long, Yang, Guan, Yu & Shao, Ling (2019). Generic compact representation through visual-semantic ambiguity removal. PATTERN RECOGNITION LETTERS 117: 186-192.
- Zhang, Haofeng, Long, Yang & Shao, Ling (2019). Zero-shot Hashing with orthogonal projection for image retrieval. PATTERN RECOGNITION LETTERS 117: 201-209.
- Zhang, Haofeng, Long, Yang & Zhao, Chunxia (2018). Attribute relaxation from class level to instance level for zero-shot learning. ELECTRONICS LETTERS 54(20): 1170-1171.
- Long, Yang, Zhu, Fan, Shao, Ling & Han, Junwei (2018). Face recognition with a small occluded training set using spatial and statistical pooling. INFORMATION SCIENCES 430: 634-644.
- Long, Yang, Guan, Yu & Shao, Ling (2018). Generic compact representation through visual-semantic ambiguity removal. Pattern Recognition Letters 186: 192.
- Zhang, Haofeng, Liu, Li, Long, Yang & Shao, Ling (2018). Unsupervised Deep Hashing With Pseudo Labels for Scalable Image Retrieval. IEEE TRANSACTIONS ON IMAGE PROCESSING 27(4): 1626-1638.
- Zhang, Haofeng, Long, Yang & Shao, Ling (2018). Zero-shot leaning and hashing with binary visual similes. Multimedia Tools and Applications 1-19.
- Long, Yang, Zhu, Fan & Shao, Ling (2016). Recognising occluded multi-view actions using local nearest neighbour embedding. Computer Vision and Image Understanding 144: 36-45.
- 2018: MRC Innovation Fellow