Smart Farming: Automatic Detection and Classification of Olive Leaf Diseases

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Author(s): Imen Fourati Kallel (Ecole Nationale d'Electronique et des Télécommunications de Sfax (ENET'Com), Tunisia), Mohamed Kallel (Ecole Nationale d'Electronique et des Télécommunications de Sfax (ENET'Com), Tunisia), Mahmoud Ghorbel (Centre de Recherche en Numérique de Sfax (CRNS), Tunisia)and Mohamed Ali Triki (The Olive Tree Institute of Tunisia, Tunisia)
Copyright: 2023
Pages: 23
Source title: Handbook of Research on AI Methods and Applications in Computer Engineering
Source Author(s)/Editor(s): Sanaa Kaddoura (Zayed University, UAE)
DOI: 10.4018/978-1-6684-6937-8.ch015

Keywords: Artificial Intelligence / Computer Engineering / Computer Science & IT / Engineering Science Reference

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Abstract

Olive trees diseases harm the quality and the quantity of the harvest seriously, which causes considerable economic losses for farmers, and more importantly affects the national economy in its entirety. The aim of this investigation is to work out a recognizing pattern method, based on the analysis of the texture and supervised classification. It essentially detects and classifies olive tree diseases in order to provide the farmers with tools helping them not only to get informed of their trees' diseases, but also to know how to treat them effectively.

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Smart Farming: Automatic Detection and Classification of Olive Leaf Diseases

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