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All Journal Indonesian Journal of Electrical Engineering and Computer Science
Obagbuwa, Ibidun Christiana
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Automatic wildlife species identification on camera trap images using deep learning approaches: a systematic review Mamapule, Siyabonga; Esiefarienrhe, Bukohwo Michael; Obagbuwa, Ibidun Christiana
Indonesian Journal of Electrical Engineering and Computer Science Vol 40, No 2: November 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v40.i2.pp968-977

Abstract

The foundation of systematic research depends on precise species identification, functioning as a critical component in the processes of biological research. Wildlife biologists are prompting for more effective techniques to fulfill the expanding need for species identification. The rise in open source image data showing animal species, captured by digital cameras and other digital methods of collecting data, has been monumental. This rapid expansion of animal image data, integrated with state-of-the-art machine learning techniques such as deep learning which has shown significant capabilities for automating species identification. This paper focuses on the role of deep neural network architectures in furthering technological advancements in automating species identification in recent years. To advocate further investigation in this field, an examination of machine learning architectures for species identification was presented in this work. This examination focuses primarily on image analyses and discusses their significance in wildlife conservation. Fundamentally, the aim of this article is to offer insights into the present advancements in automating species identification and to act as a reference for scholars who are keen to integrate machine learning techniques into ecological studies. Systems designed through Artificial Intelligence are extensive in providing toolkits for systematic identification of species in the upcoming years.
Co-Authors Esiefarienrhe, Bukohwo Michael Mamapule, Siyabonga