Items where Author is "Mohmed, G"

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Number of items: 10.

Journal article

MOHMED, G., HEYNES, X., NASER, A., SUN, W., HARDY, K., GRUNDY, S. and LU, C., 2023. Modelling daily plant growth response to environmental conditions in Chinese solar greenhouse using Bayesian neural network. Scientific Reports, 13 (1): 4379. ISSN 2045-2322

MOHMED, G., LOTFI, A. and POURABDOLLAH, A., 2020. Enhanced fuzzy finite state machine for human activity modelling and recognition. Journal of Ambient Intelligence and Humanized Computing. ISSN 1868-5137

MOHMED, G., LOTFI, A. and POURABDOLLAH, A., 2020. Convolutional neural network classifier with fuzzy feature representation for human activity modelling. .

MOHMED, G., LOTFI, A. and POURABDOLLAH, A., 2018. Human activities recognition based on neuro-fuzzy finite state machine. Technologies, 6 (4): 110. ISSN 2227-7080

Chapter in book

MOHMED, G., GRUNDY, S., LOTFI, A. and LU, C., 2022. Using AI approaches for predicting tomato growth in hydroponic systems. In: T. JANSEN, R. JENSEN, N. MACPARTHALÁIN and C.M. LIN, eds., Advances in computational intelligence systems. Contributions presented at the 20th UK Workshop on Computational Intelligence, September 8-10, 2021, Aberystwyth, Wales, UK. Advances in intelligent systems and computing (1409). Cham: Springer, pp. 277-287. ISBN 9783030870935

MOHMED, G., LOTFI, A. and POURABDOLLAH, A., 2020. Employing a deep convolutional neural network for human activity recognition based on binary ambient sensor data. In: PETRA '20: Proceedings of the 13th ACM International Conference on PErvasive Technologies Related to Assistive Environments. New York: Association for Computing Machinery (ACM), pp. 1-7. ISBN 9781450377737

MOHMED, G., ADAMA, D.A. and LOTFI, A., 2019. Fuzzy feature representation with bidirectional long short-term memory for human activity modelling and recognition. In: Z. JU, L. YANG, C. YANG, A. GEGOV and D. ZHOU, eds., Advances in computational intelligence systems. UKCI 2019. Advances in intelligent systems and computing (1043). Cham: Springer, pp. 15-26. ISBN 9783030299323

MOHMED, G., LOTFI, A. and POURABDOLLAH, A., 2019. Long short-term memory fuzzy finite state machine for human activity modelling. In: Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments - PETRA '19, Rhodes, Greece, 5-7 June 2019. New York: ACM, pp. 561-567. ISBN 9781450362320

MOHMED, G., LOTFI, A., LANGENSIEPEN, C. and POURABDOLLAH, A., 2018. Clustering-based fuzzy finite state machine for human activity recognition. In: A. LOTFI, H. BOUCHACHIA, A. GEGOV, C. LANGENSIEPEN and M. MCGINNITY, eds., Advances in computational intelligence systems: contributions presented at the 18th UK Workshop on Computational Intelligence, September 5-7, 2018, Nottingham, UK. Advances in intelligent systems and computing (AISC), 840 . Cham, Switzerland: Springer, pp. 264-275. ISBN 9783319979816

MOHMED, G., LOTFI, A., LANGENSIEPEN, C. and POURABDOLLAH, A., 2018. Unsupervised learning fuzzy finite state machine for human activities recognition. In: Proceedings of the 11th International Conference on PErvasive Technologies Related to Assistive Environments, PETRA '18, Corfu, Greece, 26-29 June 2018. New York: ACM, pp. 537-544. ISBN 9781450363907

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