default author photo

Mokhtar Dhibi

affiliation not provided to SSRN

  • affiliation not provided to SSRN

SCHOLARLY PAPERS

1

DOWNLOADS

10

TOTAL CITATIONS

0

Scholarly Papers (1)

Actions:
Email selected abstracts
1.

A Convolutional Neural Network-Based Machine Learning Prototype for Accurate Identification of Five HyalommaTick Species in Tunisia: Development and Assessment of an Experimental Prototype

Number of pages: 38 Posted: 01 Jul 2026
Essia Sebai, Nour Elhouda Habessi, anis ben aicha, Habib Fathallah, Amairia Amairia, Amani Jomli, Rihab Romdhane, Mokhtar Dhibi, Amine Mosbah, Mourad Ben Said, Moez Mhadhbi and Mohamed Aziz Darghouth
affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, University of Carthage - Faculté des Sciences de Bizerte, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, University of Manouba, affiliation not provided to SSRN and affiliation not provided to SSRN
Downloads 10

Abstract:

Loading...

Hyalomma ticks, Artificial intelligence, Deep learning, Convolutional neural network, Automated tick identification, One Health surveillance