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UAV spraying on citrus crop: impact of tank-mix adjuvant on the contact angle and droplet distribution
Meng, Y., Zhong, W., Liu, C., Su, J., Su, J., Lan, Y., Wang, Z., Wang, M.
PeerJ, vol. 10, 13064
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https://doi.org/10.7717/peerj.13064
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http://aura.abdn.ac.uk/bitstream/2164/18485/1/Meng_etal_PeerJ_UAV_spraying_on_VOR.pdf
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Smart Hospital Innovation: Technology, Service, and Policy
Hu, H., Su, J., Ma, J.
Frontiers in public health, vol. 10, 845577
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https://doi.org/10.3389/fpubh.2022.845577
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http://aura.abdn.ac.uk/bitstream/2164/18529/1/Hu_etal_Smart_hospital_innovation_VOR.pdf
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A multi-sensory stimulating attention model for cities' taxi service demand prediction
Liao, L., Wang, Y., Zou, F., Bi, S., Su, J., Sun, Q.
Scientific Reports, vol. 12, no. 1, 3065
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https://doi.org/10.1038/s41598-022-07072-z
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http://aura.abdn.ac.uk/bitstream/2164/18520/1/Liao_etal_SR_a_multi_sensory_stimulating_VOR.pdf
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Snow Coverage Mapping by Learning from Sentinel-2 Satellite Multispectral Images via Machine Learning Algorithms
Wang, Y., Su, J., Zhai, X., Meng, F., Liu, C.
Remote Sensing, vol. 14, no. 3, 782
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https://doi.org/10.3390/rs14030782
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http://aura.abdn.ac.uk/bitstream/2164/18484/1/Wang_etal_Snow_coverage_mapping_VOR.pdf
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The Role of Cross-Silo Federated Learning in Facilitating Data Sharing in the Agri-Food Sector
Durrant, A., Markovic, M., Matthews, D., May, D., Enright, J., Leontidis, G.
Computers and Electronics in Agriculture, vol. 193, 106648
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https://doi.org/10.1016/j.compag.2021.106648
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http://aura.abdn.ac.uk/bitstream/2164/19756/1/Durrant_etal_CEA_The_Role_Of_AAM.pdf
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Cooperative Multiagent Attentional Communication for Large-Scale Task Space
Zou, Q., Hu, Y., Yi, D., Gao, B., Qin, J., Chen, C. (ed.)
Wireless Communications and Mobile Computing, vol. 2022, 4401653
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https://doi.org/10.1155/2022/4401653
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http://aura.abdn.ac.uk/bitstream/2164/17831/1/Zou_etal_WCMC_Cooperative_multi_agent_attentional_AAM.pdf
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http://aura.abdn.ac.uk/bitstream/2164/17831/3/Zou_etal_Cooperative_multiagent_task_VOR.pdf
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Diversity-Augmented Intrinsic Motivation for Deep Reinforcement Learning
Dai, T., Du, Y., Fang, M., Bharath, A. A.
Neurocomputing, vol. 468, pp. 396-406
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https://doi.org/10.1016/j.neucom.2021.10.040
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http://dx.doi.org/10.1016/j.neucom.2021.10.040
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Spectral analysis and mapping of blackgrass weed by leveraging machine learning and UAV multispectral imagery
Su, J., Yi, D., Coombes, M., Liu, C., Zhai, X., McDonald-Maier, K., Chen, W. H.
Computers and Electronics in Agriculture, vol. 192, 106621
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https://doi.org/10.1016/j.compag.2021.106621
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http://aura.abdn.ac.uk/bitstream/2164/19678/1/Su_etal_CEA_Spectral_Analysis_And_AAM.pdf
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View publication in Scopus
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Attention integrated hierarchical networks for no-reference image quality assessment
You, J., Korhonen, J.
Journal of Visual Communication and Image Representation, vol. 82, 103399
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https://doi.org/10.1016/j.jvcir.2021.103399
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http://aura.abdn.ac.uk/bitstream/2164/19406/1/You_etal_JVCIR_Attention_Integrated_Hierarchical_VOR.pdf
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Deep CNN based droplet deposition segmentation for spray distribution assessment
Chen, T., Meng, Y., Su, J., Liu, C.
Chapters in Books, Reports and Conference Proceedings: Conference Proceedings
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https://doi.org/10.1109/ICAC55051.2022.9911061
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http://aura.abdn.ac.uk/bitstream/2164/20930/1/Chen_etal_ICAAC2022_Deep_CNN_Based_AAM.pdf