Autonomous palm tree detection from remote sensing images-UAE dataset

Al-Saad, Mina and Aburaed, Nour and Mansoori, Saeed Al and Ahmad, Hussain Al; (2022) Autonomous palm tree detection from remote sensing images-UAE dataset. In: IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. International Geoscience and Remote Sensing Symposium (IGARSS) . Institute of Electrical and Electronics Engineers Inc., MYS, pp. 2191-2194. ISBN 9781665427920 (https://doi.org/10.1109/IGARSS46834.2022.9884126)

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Abstract

Autonomous detection and counting of palm trees is a research field of interest to various countries around the world, including the UAE. Automating this task saves effort and resources by minimizing human intervention and reducing potential errors in counting. This paper introduces a new High Resolution (HR) remote sensing dataset for autonomous detection of palm trees in the UAE. The dataset is collected using Unmanned Aerial Vehicles (UAV), and it is labeled properly in PASCAL VOC and YOLO formats after preprocessing and visually inspecting its quality. A comparative evaluation between Faster-RCNN and YOLOv4 networks is then conducted to observe the usability of the dataset in addition to the strengths and weaknesses of each network. The dataset is publicly available at https://github.com/Nour093/Palm-Tree-Dataset.

ORCID iDs

Al-Saad, Mina, Aburaed, Nour ORCID logoORCID: https://orcid.org/0000-0002-5906-0249, Mansoori, Saeed Al and Ahmad, Hussain Al;
  • Item type:Book Section
    ID code:83244
    Dates:
    Date
    Event
    28 September 2022
    Published
    22 July 2022
    Published Online
    4 April 2022
    Accepted
    Notes:© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subjects:Science > Mathematics > Electronic computers. Computer science
    Technology > Electrical engineering. Electronics Nuclear engineering
    Department:UNSPECIFIED
    Depositing user: Pure Administrator
    Date deposited:17 Nov 2022 09:49
    Last modified:21 Nov 2024 01:31
    URI:https://strathprints.strath.ac.uk/id/eprint/83244
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