Drone Applications in Logistics and Supply Chain Management: A Systematic Review Using Latent Dirichlet Allocation
Author:
Funder
University of Jeddah
Publisher
Springer Science and Business Media LLC
Subject
Multidisciplinary
Link
https://link.springer.com/content/pdf/10.1007/s13369-023-08681-0.pdf
Reference77 articles.
1. Rejeb, A.; Rejeb, K.; Simske, S.J.; Treiblmaier, H.: Drones for supply chain management and logistics: a review and research agenda. Int. J. Logist. Res. Appl. (2021). https://doi.org/10.1080/13675567.2021.1981273
2. Aggarwal, A.K.: Fusion and Enhancement Techniques for Processing of Multispectral Images. In: Avtar, R.; Watanabe, T. (Eds.) Unmanned Aerial Vehicle: Applications in Agriculture and Environment, pp. 159–175. Springer International Publishing, Cham (2020)
3. Lemardelé, C.; Estrada, M.; Pagès, L.; Bachofner, M.: Potentialities of drones and ground autonomous delivery devices for last-mile logistics. Transp. Res. Part E Logist. Transp. Rev. (2021). https://doi.org/10.1016/j.tre.2021.102325
4. Xiao, J.; Suab, S.A.; Chen, X.; Singh, C.K.; Singh, D.; Aggarwal, A.K.; Korom, A.; Widyatmanti, W.; Mollah, T.H.; Minh, H.V.T.; Khedher, K.M.; Avtar, R.: Enhancing assessment of corn growth performance using unmanned aerial vehicles (UAVs) and deep learning. Measurement 214, 112764 (2023). https://doi.org/10.1016/j.measurement.2023.112764
5. Damoah, I.S.; Ayakwah, A.; Tingbani, I.: Artificial intelligence (AI)-enhanced medical drones in the healthcare supply chain (HSC) for sustainability development: A case study. J. Clean. Prod. (2021). https://doi.org/10.1016/j.jclepro.2021.129598
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