@inproceedings{a4307da5e38d43079d69eccc213caf5f,
title = "Autonomous palm tree detection from remote sensing images-UAE dataset",
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.",
keywords = "convolutional neural networks (CNN), FRCNN, object detection, remote sensing, YOLOv4",
author = "Mina Al-Saad and Nour Aburaed and Mansoori, {Saeed Al} and Ahmad, {Hussain Al}",
note = "{\textcopyright} 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.; 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022 ; Conference date: 17-07-2022 Through 22-07-2022",
year = "2022",
month = sep,
day = "28",
doi = "10.1109/IGARSS46834.2022.9884126",
language = "English",
isbn = "9781665427937",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
pages = "2191--2194",
booktitle = "IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium",
}