Articles | Volume 68, issue 3
https://doi.org/10.5194/aab-68-473-2025
https://doi.org/10.5194/aab-68-473-2025
Original study
 | 
14 Jul 2025
Original study |  | 14 Jul 2025

Deep-learning-based buffalo identification through muzzle pattern images

Orhan Ermetin and Humar Kahramanlı Örnek

Viewed

Total article views: 276 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
230 32 14 276 26 33
  • HTML: 230
  • PDF: 32
  • XML: 14
  • Total: 276
  • BibTeX: 26
  • EndNote: 33
Views and downloads (calculated since 14 Jul 2025)
Cumulative views and downloads (calculated since 14 Jul 2025)

Viewed (geographical distribution)

Total article views: 276 (including HTML, PDF, and XML) Thereof 276 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 28 Aug 2025
Short summary

The study utilises artificial intelligence to improve buffalo recognition in livestock management. It employs facial images of 11 buffaloes to develop a dataset and utilises four CNN (convolutional neural network) algorithms to identify buffaloes based on muzzle patterns. Results indicate successful performance, with SqueezeNet achieving the highest accuracy of 99.88 %, along with high precision, recall, and F1 score.

Share