Items where Author is "Mohmed, G"
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., 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., LOTFI, A. and POURABDOLLAH, A., 2020. Convolutional neural network classifier with fuzzy feature representation for human activity modelling. In: 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE): 2020 conference proceedings. Piscataway, NJ: IEEE. ISBN 9781728169323
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
Conference contribution
LU, C. and MOHMED, G., 2023. Artificial Intelligence (AI) leads vertical farming and urban agriculture. In: 2nd International Workshop on Vertical Farming (VertiFarm 2023), Chengdu, China, 22-24 May 2023.