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An interactive evolution strategy based deep convolutional generative adversarial network for 2D video game level procedural content generation. (2021)
Conference Proceeding
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)
Conference Proceeding
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..

In-house deep environmental sentience for smart homecare solutions toward ageing society. (2020)
Conference Proceeding
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)
Conference Proceeding
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..