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Multi-head attention-based long short-term memory for depression detection from speech. (2021)
Journal Article
ZHAO, Y., LIANG, Z., DU, J., ZHANG, L., LIU, C. and ZHAO, L. 2021. Multi-head attention-based long short-term memory for depression detection from speech. Frontiers in neurorobotics [online], 15, article 684037. Available from: https://doi.org/10.3389/fnbot.2021.684037

Depression is a mental disorder that threatens the health and normal life of people. Hence, it is essential to provide an effective way to detect depression. However, research on depression detection mainly focuses on utilizing different parallel fea... Read More about Multi-head attention-based long short-term memory for depression detection from speech..

Modeling and dynamic analysis of spiral bevel gear coupled system of intermediate and tail gearboxes in a helicopter. (2021)
Journal Article
ZHU, H., CHEN, W., ZHU, R., ZHANG, L., FU, B. and LU, X. 2021. Modeling and dynamic analysis of spiral bevel gear coupled system of intermediate and tail gearboxes in a helicopter. Proceedings of the Institution of Mechanical Engineers, part C: journal of mechanical engineering science [online], 235(22), pages 5975-5993. Available from: https://doi.org/10.1177/0954406221992798

The coupled dynamic model of the intermediate and tail gearboxes’ spiral bevel gear-oblique tail shaft-laminated membrane coupling was established by employing the hybrid modeling method of finite element and lumped mass. Among them, the dynamic equa... Read More about Modeling and dynamic analysis of spiral bevel gear coupled system of intermediate and tail gearboxes in a helicopter..

Intelligent human action recognition using an ensemble model of evolving deep networks with swarm-based optimization. (2021)
Journal Article
ZHANG, L., LIM, C.P. and YU, Y. 2021. Intelligent human action recognition using an ensemble model of evolving deep networks with swarm-based optimization. Knowledge-based systems [online], 220, article ID 106918. Available from: https://doi.org/10.1016/j.knosys.2021.106918

Automatic interpretation of human actions from realistic videos attracts increasing research attention owing to its growing demand in real-world deployments such as biometrics, intelligent robotics, and surveillance. In this research, we propose an e... Read More about Intelligent human action recognition using an ensemble model of evolving deep networks with swarm-based optimization..

Feature selection using enhanced particle swarm optimisation for classification models. (2021)
Journal Article
XIE, H., ZHANG, L., LIM, C.P., YU, Y. and LIU, H. 2021. Feature selection using enhanced particle swarm optimisation for classification models. Sensors [online], 21(5), article 1816. Available from: https://doi.org/10.3390/s21051816

In this research, we propose two Particle Swarm Optimisation (PSO) variants to undertake feature selection tasks. The aim is to overcome two major shortcomings of the original PSO model, i.e., premature convergence and weak exploitation around the ne... Read More about Feature selection using enhanced particle swarm optimisation for classification models..

Particle swarm optimization for automatically evolving convolutional neural networks for image classification. (2021)
Journal Article
LAWRENCE, T., ZHANG, L., LIM, C.P. and PHILLIPS, E.-J. 2021. Particle swarm optimization for automatically evolving convolutional neural networks for image classification. IEEE access [online], 9, pages 14369-14386. Available from: https://doi.org/10.1109/ACCESS.2021.3052489

Designing Convolutional Neural Networks from scratch is a time-consuming process that requires specialist expertise. While automated architecture generation algorithms have been proposed, the underlying search strategies generally are computationally... Read More about Particle swarm optimization for automatically evolving convolutional neural networks for image classification..