All Outputs (10)

HyperDehazing: a hyperspectral image dehazing benchmark dataset and a deep learning model for haze removal. (2024)
Journal Article
FU, H., LING, Z., SUN, G., REN, J., ZHANG, A., ZHANG, L. and JIA, X. 2024. HyperDehazing: a hyperspectral image dehazing benchmark dataset and a deep learning model for haze removal. ISPRS journal of photogrammetry and remote sensing [online], 218(part A), pages 663-677. Available from: https://doi.org/10.1016/j.isprsjprs.2024.09.034

Haze contamination severely degrades the quality and accuracy of optical remote sensing (RS) images, including hyperspectral images (HSIs). Currently, there are no paired benchmark datasets containing hazy and haze-free scenes in HSI dehazing, and fe... Read More about HyperDehazing: a hyperspectral image dehazing benchmark dataset and a deep learning model for haze removal..

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..

An interactive evolution strategy based deep convolutional generative adversarial network for 2D video game level procedural content generation. (2021)
Presentation / Conference Contribution
JIANG, M. and ZHANG, L. 2021. An interactive evolution strategy based deep convolutional generative adversarial network for 2D video game level procedural content generation. In Proceedings of 2021 International joint conference on neural networks (IJCNN 2021), 18-22 July 2021, [virtual conference]. Piscataway: IEEE [online], article 9533847. Available from: https://doi.org/10.1109/IJCNN52387.2021.9533847

The generation of desirable video game contents has been a challenge of games level design and production. In this research, we propose a game player flow experience driven interactive latent variable evolution strategy incorporated with a Deep Convo... Read More about An interactive evolution strategy based deep convolutional generative adversarial network for 2D video game level procedural content generation..

Deep recurrent neural networks with attention mechanisms for respiratory anomaly classification. (2021)
Presentation / Conference Contribution
WALL, C., ZHANG, L., YU, Y. and MISTRY, K. 2021. Deep recurrent neural networks with attention mechanisms for respiratory anomaly classification. In Proceedings of 2021 International joint conference on neural networks (IJCNN 2021), 18-22 July 2021, [virtual conference]. Piscataway: IEEE [online], article 9533966. Available from: https://doi.org/10.1109/IJCNN52387.2021.9533966

In recent years, a variety of deep learning techniques and methods have been adopted to provide AI solutions to issues within the medical field, with one specific area being audio-based classification of medical datasets. This research aims to create... Read More about Deep recurrent neural networks with attention mechanisms for respiratory anomaly classification..

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..

In-house deep environmental sentience for smart homecare solutions toward ageing society. (2020)
Presentation / Conference Contribution
EASOM, P., BOURIDANE, A., QIANG, F., DOWNS, C. and JIANG, R. 2020. In-house deep environmental sentience for smart homecare solutions toward ageing society. In Proceedings of 2020 International conference machine learning and cybernetics (ICMLC 2020), 4 December 2020, [virtual conference]. Piscataway: IEEE [online], pages 261-266. Available from: https://doi.org/10.1109/ICMLC51923.2020.9469531

With an increasing amount of elderly people needing home care around the clock, care workers are not able to keep up with the demand of providing maximum support to those who require it. As medical costs of home care increase the quality is care suff... Read More about In-house deep environmental sentience for smart homecare solutions toward ageing society..

Object recognition using enhanced particle swarm optimization. (2020)
Presentation / Conference Contribution
WILLIS, M., ZHANG, L., LIU, H., XIE, H. and MISTRY, L. 2020. Object recognition using enhanced particle swarm optimization. In Proceedings of 2020 International conference machine learning and cybernetics (ICMLC 2020), 4 December 2020, [virtual conference]. Piscataway: IEEE [online], pages 241-246. Available from: https://doi.org/10.1109/ICMLC51923.2020.9469584

The identification of the most discriminative features in an explainable AI decision-making process is a challenging problem. This research tackles such challenges by proposing Particle Swarm Optimization (PSO) variants embedded with novel mutation a... Read More about Object recognition using enhanced particle swarm optimization..