cff-version: 1.2.0
abstract: "<p>This dataset supports the PhD research titled <em>“AI in the Sky: Advancing Wildlife Survey Methods in Africa with Deep Learning and Aerial Imagery”</em>. The research aims to improve wildlife monitoring through deep learning and remote sensing. It focuses on object detection and species counting based on aerial surveys over African wildlife reserves. The dataset includes the Aerial Elephant Dataset (AED) annotations, for which bounding boxes in standard VOC format were created to supplement the original point annotations, and an Antelope Dataset provided by African Parks in South Sudan under a research agreement. These annotations support the training and validation of deep learning models such as YOLO, RT-DETR, CenterNet, U-Net, and D2-Net. Supporting scripts for processing, tiling, annotation handling, quality control, and statistical analysis are included to ensure reproducibility.</p>"
authors:
  - family-names: Xu
    given-names: Zeyu
    orcid: "https://orcid.org/0000-0002-7695-3356"
title: "Data underlying PhD thesis: AI in the Sky - Advancing Wildlife Survey Methods in Africa with Deep Learning and Aerial Imagery"
keywords:
version: 1
identifiers:
  - type: doi
    value: 10.4121/838e8d53-e7ba-4306-a62c-6ba7a9428f13.v1
license: CC BY-NC-ND 4.0
date-released: 2025-06-30