@inproceedings{ee66c14b3741478790f5e3263734e7ea,
title = "Autonomous localization of the best depth blob using TOPSIS: application on forage plants for the Sharjah pastures project",
abstract = "This research constitutes a building block in a larger decision support system, which combines computer vision and multi-criteria decision making, to identify indigenous forage plants in close-range aerial images. Such a system enables managing the open pastures project of the Emirate of Sharjah, United Arab Emirates (UAE). The system aims at the identification of forage plants through the detection of plant inflorescences in depth images, and applying TOPSIS, to select and localize the best plant inflorescence.",
keywords = "Blobs, Cenchrus ciliaris, Computer Vision, DSS, Decision Making Process, Decision Support System, Depth, Pennisetum divisum, Plant Identification, TOPSIS, forage",
author = "Radhwan Sani and Ali Cheaitou and Tamer Rabie",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 14th International Conference on Developments in eSystems Engineering, DeSE 2021 ; Conference date: 07-12-2021 Through 10-12-2021",
year = "2021",
doi = "10.1109/DESE54285.2021.9719515",
language = "English",
series = "Proceedings - International Conference on Developments in eSystems Engineering, DeSE",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "394--400",
booktitle = "2021 14th International Conference on Developments in eSystems Engineering, DeSE 2021",
address = "United States",
}