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Development of a mobile application for identification of grapevine (Vitis vinifera L.) cultivars via deep learning
2021
Liu, Y., Su, J., Shen, L., Lu, N., Fang, Y., Liu, F., Song, Y., Su, B.
International journal of agricultural and biological engineering , vol. 14, no. 5, pp. 172-179
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https://doi.org/10.25165/j.ijabe.20211405.6593
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http://aura.abdn.ac.uk/bitstreams/22090d9b-3f2c-4017-a978-82588534eed0/download
Dynamic multi-objective optimization algorithm based decomposition and preference
2021
Hu, Y., Zheng, J., Zou, J., Jiang, S., Yang, S.
Information Sciences , vol. 571, pp. 175-190
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https://doi.org/10.1016/j.ins.2021.04.055
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Transformer For Image Quality Assessment
2021
You, J., Korhonen, J.
Chapters in Books, Reports and Conference Proceedings: Conference Proceedings
Online
https://arxiv.org/abs/2101.01097
Digital Object Identifier
https://doi.org/10.1109/ICIP42928.2021.9506075
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Commentary to the Commission’s proposal for the “AI Act” – Response to selected issues
2021
Cserne, P., Ducato, R., Zivkovic, P., Brown, A., Couzigou, I., Leontidis, G., Oren, N., Sutherland, C., Sweeney, P., Yuksel Ripley, B.
Non-textual Forms: Web Publications and Websites
Online
https://ec.europa.eu/info/law/better-regulation/have-your-say/initiatives/12527-Artificial-intelligence-ethical-and-legal-requirements/F2665397_en
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https://ec.europa.eu/info/law/better-regulation/have-your-say/initiatives/12527-Artificial-intelligence-ethical-and-legal-requirements_en
Solving dynamic multi-objective problems with a new prediction-based optimization algorithm
2021
Zhang, Q., Jiang, S., Yang, S., Song, H.
PloS ONE , vol. 16, no. 8 August, e0254839
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https://doi.org/10.1371/journal.pone.0254839
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http://aura.abdn.ac.uk/bitstreams/0f9840cc-d43a-42a5-9b9e-6791497aa225/download
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Adaptive Inverse Control of a Vibrating Coupled Vessel-Riser System With Input Backlash
2021
He, X., Zhao, Z., Su, J., Yang, Q., Zhu, D.
IEEE Transactions on Systems, Man, and Cybernetics: Systems , vol. 51, no. 8, pp. 4706 - 4715
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Digital Object Identifier
https://doi.org/10.1109/TSMC.2019.2944999
Deep Learning for Computer-Aided Diagnosis in Ophthalmology: A Review
2021
Brown, J., Leontidis, G.
State of the Art in Neural Networks and Their Applications . El-Baz, S., Suri, J. S. (eds.). 1st edition. Elsevier, pp. 219-237, 19 pages
Chapters in Books, Reports and Conference Proceedings: Chapters
Digital Object Identifier
https://doi.org/10.1016/B978-0-12-819740-0.00011-5
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https://www.elsevier.com/books/state-of-the-art-in-neural-networks-and-their-applications/s-el-baz/978-0-12-819740-0
Deep learning based prediction on greenhouse crop yield combined TCN and RNN
2021
Gong, L., Yu, M., Jiang, S., Cutsuridis, V., Pearson, S.
Sensors , vol. 21, no. 13, 4537
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Digital Object Identifier
https://doi.org/10.3390/s21134537
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http://aura.abdn.ac.uk/bitstreams/aa73735b-bace-4e4c-b9f8-c1cafeea59a2/download
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The short-term associations of chronic obstructive pulmonary disease hospitalizations with meteorological factors and air pollutants in Southwest China: a time-series study
2021
Li, M., Chen, S., Zhao, H., Tang, C., Lai, Y., Ung, C. O. L., Su, J., Hu, H.
Scientific Reports , vol. 11, no. 1, 12914
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https://doi.org/10.1038/s41598-021-92380-z
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http://aura.abdn.ac.uk/bitstreams/d3423228-fa98-4d82-b54a-47ee1e861927/download
An autoencoder wavelet based deep neural network with attention mechanism for multi-step prediction of plant growth
2021
Alhnaity, B., Kollias, S., Leontidis, G., Jiang, S., Schamp, B., Pearson, S.
Information Sciences , vol. 560, pp. 35-50
Contributions to Journals: Articles
Digital Object Identifier
https://doi.org/10.1016/j.ins.2021.01.037
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http://aura.abdn.ac.uk/bitstreams/13e0f06c-e2b6-4190-8123-ae617c1b1251/download
