Open access
Sep 2026
A convolutional neural network-based machine learning prototype for accurate identification of five Hyalomma tick species in Tunisia: Development and assessment of an experimental prototype.
Accurate tick species identification is essential for vector surveillance and control of tick-borne diseases, but conventional morphological diagnosis remains challenging for closely related Hyalomma species. This study developed and evaluated a deep learning-based framework for automated recognition of five medically...
E. Sebai, Nour Elhouda Habessi, A. Ben Aicha et al.
· Veterinary parasitology · 0 citations