Automated Wildlife Species Detection and Classification in Oman’s Natural Reserves Using Few-Shot Learning
Date
2025-06-01
Authors
Ethar Tamimi
Malak Abdul Hamid Al Hinai
Iman Said Al Hajri
Abdelhamid Abdessalem
Journal Title
Journal ISSN
Volume Title
Publisher
Deanship of Research - Al-Quds University
Abstract
Background: Wildlife monitoring is a critical component of biodiversity conservation, especially in regions like Oman, where ecological challenges and human-induced threats endanger various species. Camera traps have become invaluable tools for capturing wildlife activity, producing large volumes of image data over time. However, manually analyzing these images is labor-intensive, time-consuming, and prone to human error. Accurate species detection and recognition are essential for informing effective conservation strategies, yet traditional methods of reviewing images present limitations.