An investigation of lightweight AI models to classify African ungulate species from tracks
- DOI
- 10.1016/j.ecoinf.2025.103393
- Published
- 2025-12
- Container
- Ecological Informatics
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.ecoinf.2025.103393,
title = {An investigation of lightweight AI models to classify African ungulate species from tracks},
author = {Tinao Petso and Rodrigo S. Jamisola and Sky Alibhai and Molaletsa Namoshe and Wazha Mmereki and Zoe Jewell},
year = {2025},
journal = {Ecological Informatics},
doi = {10.1016/j.ecoinf.2025.103393},
url = {https://doi.org/10.1016/j.ecoinf.2025.103393}
}RIS
TY - JOUR TI - An investigation of lightweight AI models to classify African ungulate species from tracks AU - Tinao Petso AU - Rodrigo S. Jamisola AU - Sky Alibhai AU - Molaletsa Namoshe AU - Wazha Mmereki AU - Zoe Jewell PY - 2025 JO - Ecological Informatics DO - 10.1016/j.ecoinf.2025.103393 UR - https://doi.org/10.1016/j.ecoinf.2025.103393 ER -
APA
Petso, T., Jamisola, R. S., Alibhai, S., Namoshe, M., Mmereki, W., & Jewell, Z. (2025). An investigation of lightweight AI models to classify African ungulate species from tracks. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2025.103393
Source records
- crossref · retrieved 2026-09-26T10:13:35.220Z