Joint multi-label learning and feature extraction for temporal link prediction
(2022)
Journal Article
Ma, X., Tan, S., Xie, X., Zhong, X., & Deng, J. (2022). Joint multi-label learning and feature extraction for temporal link prediction. Pattern Recognition, 121, https://doi.org/10.1016/j.patcog.2021.108216
Outputs (31)
Sampling strategies for learning-based 3D medical image compression (2022)
Journal Article
Nagoor, O. H., Whittle, J., Deng, J., Mora, B., & Jones, M. W. (2022). Sampling strategies for learning-based 3D medical image compression. https://doi.org/10.1016/j.mlwa.2022.100273
GRNN: generative regression neural network—a data leakage attack for federated learning (2022)
Journal Article
Ren, H., Deng, J., & Xie, X. (2022). GRNN: generative regression neural network—a data leakage attack for federated learning. ACM Transactions on Intelligent Systems and Technology, 13(4), 1-24. https://doi.org/10.1145/3510032
Crowd Counting via Segmentation Guided Attention Networks and Curriculum Loss (2022)
Journal Article
Wang, Q., & Breckon, T. (online). Crowd Counting via Segmentation Guided Attention Networks and Curriculum Loss. IEEE Transactions on Intelligent Transportation Systems, https://doi.org/10.1109/tits.2021.3138896Automatic crowd behaviour analysis is an important task for intelligent transportation systems to enable effective flow control and dynamic route planning for varying road participants. Crowd counting is one of the keys to automatic crowd behaviour a... Read More about Crowd Counting via Segmentation Guided Attention Networks and Curriculum Loss.
Using Model Explanations to Guide Deep Learning Models Towards Consistent Explanations for EHR Data (2022)
Journal Article
Watson, M., Awwad Shekh Hasan, B., & Al Moubayed, N. (2022). Using Model Explanations to Guide Deep Learning Models Towards Consistent Explanations for EHR Data. Scientific Reports, 12(19899), Article 19899. https://doi.org/10.1038/s41598-022-24356-6It has been shown that identical Deep Learning (DL) architectures will produce distinct explanations when trained with different hyperparameters that are orthogonal to the task (e.g. random seed, training set order). In domains such as healthcare and... Read More about Using Model Explanations to Guide Deep Learning Models Towards Consistent Explanations for EHR Data.
Cooperative Adaptive Cruise Control for Connected Autonomous Vehicles using Spring Damping Energy Model (2022)
Journal Article
Xie, S., Hu, J., Ding, Z., & Arvin, F. (2023). Cooperative Adaptive Cruise Control for Connected Autonomous Vehicles using Spring Damping Energy Model. IEEE Transactions on Vehicular Technology, 72(3), 2974 - 2987. https://doi.org/10.1109/tvt.2022.3218575
A Novel Time-of-Flight Range and Bearing Sensor System for Micro Air Vehicle Swarms (2022)
Book Chapter
Bilaloğlu, C., Şahin, M., Arvin, F., Şahin, E., & Turgut, A. E. (in press). A Novel Time-of-Flight Range and Bearing Sensor System for Micro Air Vehicle Swarms. In Swarm Intelligence. https://doi.org/10.1007/978-3-031-20176-9_20
Optimization of a Self-organized Collective Motion in a Robotic Swarm (2022)
Book Chapter
Bahaidarah, M., Bana, F. R., Turgut, A. E., Marjanovic, O., & Arvin, F. (in press). Optimization of a Self-organized Collective Motion in a Robotic Swarm. In Swarm Intelligence. https://doi.org/10.1007/978-3-031-20176-9_31
Design and Experimental Validation of Deep Reinforcement Learning-Based Fast Trajectory Planning and Control for Mobile Robot in Unknown Environment (2022)
Journal Article
Chai, R., Niu, H., Carrasco, J., Arvin, F., Yin, H., & Lennox, B. (2024). Design and Experimental Validation of Deep Reinforcement Learning-Based Fast Trajectory Planning and Control for Mobile Robot in Unknown Environment. IEEE Transactions on Neural Networks and Learning Systems, 35(4), 5778-5792. https://doi.org/10.1109/tnnls.2022.3209154
A Two-stream Convolutional Network for Musculoskeletal and Neurological Disorders Prediction (2022)
Journal Article
Zhu, M., Men, Q., Ho, E. S., Leung, H., & Shum, H. P. (2022). A Two-stream Convolutional Network for Musculoskeletal and Neurological Disorders Prediction. Journal of Medical Systems, 46(11), Article 76. https://doi.org/10.1007/s10916-022-01857-5Musculoskeletal and neurological disorders are the most common causes of walking problems among older people, and they often lead to diminished quality of life. Analyzing walking motion data manually requires trained professionals and the evaluations... Read More about A Two-stream Convolutional Network for Musculoskeletal and Neurological Disorders Prediction.
CP-AGCN: Pytorch-based Attention Informed Graph Convolutional Network for Identifying Infants at Risk of Cerebral Palsy (2022)
Journal Article
Zhang, H., Ho, E. S., & Shum, H. P. (2022). CP-AGCN: Pytorch-based Attention Informed Graph Convolutional Network for Identifying Infants at Risk of Cerebral Palsy. Software impacts, 14, Article 100419. https://doi.org/10.1016/j.simpa.2022.100419Early prediction is clinically considered one of the essential parts of cerebral palsy (CP) treatment. We propose to implement a low-cost and interpretable classification system for supporting CP prediction based on General Movement Assessment (GMA).... Read More about CP-AGCN: Pytorch-based Attention Informed Graph Convolutional Network for Identifying Infants at Risk of Cerebral Palsy.
In-Materio Extreme Learning Machines (2022)
Book Chapter
Jones, B. A., Al Moubayed, N., Zeze, D. A., & Groves, C. (2022). In-Materio Extreme Learning Machines. In G. Rudolph, A. V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, & T. Tušar (Eds.), Parallel Problem Solving from Nature – PPSN XVII (505-519). Springer Verlag. https://doi.org/10.1007/978-3-031-14714-2_35Nanomaterial networks have been presented as a building block for unconventional in-Materio processors. Evolution in-Materio (EiM) has previously presented a way to congure and exploit physical materials for computation, but their ability to scale as... Read More about In-Materio Extreme Learning Machines.
Towards Intelligently Designed Evolvable Processors (2022)
Journal Article
Jones, B. A., Chouard, J. L., Branco, B. C., Vissol-Gaudin, E. G., Pearson, C., Petty, M. C., …Groves, C. (2022). Towards Intelligently Designed Evolvable Processors. Evolutionary Computation, 30(4), 479-501. https://doi.org/10.1162/evco_a_00309Evolution-in-Materio is a computational paradigm in which an algorithm reconfigures a material’s properties to achieve a specific computational function. This paper addresses the question of how successful and well performing Evolution-in-Materio pro... Read More about Towards Intelligently Designed Evolvable Processors.
Distillation of human–object interaction contexts for action recognition (2022)
Journal Article
Almushyti, M., & Li, F. W. (2022). Distillation of human–object interaction contexts for action recognition. Computer Animation and Virtual Worlds, 33(5), Article e2107. https://doi.org/10.1002/cav.2107Modeling spatial-temporal relations is imperative for recognizing human actions, especially when a human is interacting with objects, while multiple objects appear around the human differently over time. Most existing action recognition models focus... Read More about Distillation of human–object interaction contexts for action recognition.
A deep learning approach to fight illicit trafficking of antiquities using artefact instance classification (2022)
Journal Article
Winterbottom, T., Leone, A., & Al Moubayed, N. (2022). A deep learning approach to fight illicit trafficking of antiquities using artefact instance classification. Scientific Reports, 12(1), Article 13468. https://doi.org/10.1038/s41598-022-15965-2We approach the task of detecting the illicit movement of cultural heritage from a machine learning perspective by presenting a framework for detecting a known artefact in a new and unseen image. To this end, we explore the machine learning problem o... Read More about A deep learning approach to fight illicit trafficking of antiquities using artefact instance classification.
The Statistics of Eye Movements and Binocular Disparities during VR Gaming: Implications for Headset Design (2022)
Journal Article
Aizenman, A., Koulieris, G., Gibaldi, A., Sehgal, V., Levi, D., & Banks, M. S. (2023). The Statistics of Eye Movements and Binocular Disparities during VR Gaming: Implications for Headset Design. ACM Transactions on Graphics, 42(1), Article 7. https://doi.org/10.1145/3549529The human visual system evolved in environments with statistical regularities. Binocular vision is adapted to these such that depth perception and eye movements are more precise, faster, and performed comfortably in environments consistent with the r... Read More about The Statistics of Eye Movements and Binocular Disparities during VR Gaming: Implications for Headset Design.
Distributed Motion Planning for Safe Autonomous Vehicle Overtaking via Artificial Potential Field (2022)
Journal Article
Xie, S., Hu, J., Bhowmick, P., Ding, Z., & Arvin, F. (2022). Distributed Motion Planning for Safe Autonomous Vehicle Overtaking via Artificial Potential Field. IEEE Transactions on Intelligent Transportation Systems, 23(11), 21531- 21547. https://doi.org/10.1109/tits.2022.3189741Autonomous driving of multi-lane vehicle platoons have attracted significant attention in recent years due to their potential to enhance the traffic-carrying capacity of the roads and produce better safety for drivers and passengers. This paper propo... Read More about Distributed Motion Planning for Safe Autonomous Vehicle Overtaking via Artificial Potential Field.
Interaction-aware Decision-making for Automated Vehicles using Social Value Orientation (2022)
Journal Article
Crosato, L., Shum, H. P., Ho, E. S., & Wei, C. (2023). Interaction-aware Decision-making for Automated Vehicles using Social Value Orientation. IEEE Transactions on Intelligent Vehicles, 8(2), 1339-1349. https://doi.org/10.1109/tiv.2022.3189836Motion control algorithms in the presence of pedestrians are critical for the development of safe and reliable Autonomous Vehicles (AVs). Traditional motion control algorithms rely on manually designed decision-making policies which neglect the mutua... Read More about Interaction-aware Decision-making for Automated Vehicles using Social Value Orientation.
Enhanced Single Shot Small Object Detector for Aerial Imagery Using Super-Resolution, Feature Fusion and Deconvolution (2022)
Journal Article
Maktab Dar Oghaz, M., Razaak, M., & Remagnino, P. (2022). Enhanced Single Shot Small Object Detector for Aerial Imagery Using Super-Resolution, Feature Fusion and Deconvolution. Sensors, 22(12), Article 4339. https://doi.org/10.3390/s22124339
EfficientTDNN: Efficient Architecture Search for Speaker Recognition (2022)
Journal Article
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.2022.3182856Convolutional neural networks (CNNs), such as the time-delay neural network (TDNN), have shown their remarkable capability in learning speaker embedding. However, they meanwhile bring a huge computational cost in storage size, processing, and memory.... Read More about EfficientTDNN: Efficient Architecture Search for Speaker Recognition.