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A Probabilistic Zero-Shot Learning Method via Latent Nonnegative Prototype Synthesis of Unseen Classes (2019)
Journal Article
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

Zero-shot learning (ZSL), a type of structured multioutput learning, has attracted much attention due to its requirement of no training data for target classes. Conventional ZSL methods usually project visual features into semantic space and assign l... Read More about A Probabilistic Zero-Shot Learning Method via Latent Nonnegative Prototype Synthesis of Unseen Classes.

Semantic combined network for zero-shot scene parsing (2019)
Journal Article
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

Recently, image-based scene parsing has attracted increasing attention due to its wide application. However, conventional models can only be valid on images with the same domain of the training set and are typically trained using discrete and meaning... Read More about Semantic combined network for zero-shot scene parsing.

2D Pose-Based Real-Time Human Action Recognition With Occlusion-Handling (2019)
Journal Article
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

Human Action Recognition (HAR) for CCTV-oriented applications is still a challenging problem. Real-world scenarios HAR implementations is difficult because of the gap between Deep Learning data requirements and what the CCTV-based frameworks can offe... Read More about 2D Pose-Based Real-Time Human Action Recognition With Occlusion-Handling.

Few-Shot Image and Sentence Matching via Gated Visual-Semantic Embedding (2019)
Presentation / Conference Contribution
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)

Word similarity and word relatedness are fundamental to natural language processing and more generally, understanding how humans relate concepts in semantic memory. A growing number of datasets are being proposed as evaluation benchmarks,however, the... Read More about Few-Shot Image and Sentence Matching via Gated Visual-Semantic Embedding.

Depth Embedded Recurrent Predictive Parsing Network for Video Scenes (2019)
Journal Article
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

Semantic segmentation-based scene parsing plays an important role in automatic driving and autonomous navigation. However, most of the previous models only consider static images, and fail to parse sequential images because they do not take the spati... Read More about Depth Embedded Recurrent Predictive Parsing Network for Video Scenes.

Towards Reliable, Automated General Movement Assessment for Perinatal Stroke Screening in Infants Using Wearable Accelerometers (2019)
Journal Article
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

Perinatal stroke (PS) is a serious condition that, if undetected and thus untreated, often leads to life-long disability, in particular Cerebral Palsy (CP). In clinical settings, Prechtl's General Movement Assessment (GMA) can be used to classify inf... Read More about Towards Reliable, Automated General Movement Assessment for Perinatal Stroke Screening in Infants Using Wearable Accelerometers.

Attribute relaxation from class level to instance level for zero-shot learning (2018)
Journal Article
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

Conventional zero-shot learning (ZSL) methods usually use class-level attribute, which corresponds to a batch of images of same category. This setting is not reasonable since the images even though belong to same category still have variances in thei... Read More about Attribute relaxation from class level to instance level for zero-shot learning.

Triple Verification Network for Generalized Zero-Shot Learning (2018)
Journal Article
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

Conventional zero-shot learning approaches often suffer from severe performance degradation in the generalized zero-shot learning (GZSL) scenario, i.e., to recognize test images that are from both seen and unseen classes. This paper studies the Class... Read More about Triple Verification Network for Generalized Zero-Shot Learning.