The Eurasian grapevine (Vitis vinifera L.) is one of the most extensively cultivated
horticultural crop worldwide, with significant economic relevance, particularly in wine …

Many sciences exploit algorithms in a large variety of applications. In agronomy, large
amounts of agricultural data are handled by adopting procedures for optimization, clustering …

In this study, leaves, bunches and fruits of fifty grape varieties were classified using deep
learning techniques using ampelographic features. A new and unique CNN model has been …

Within the winemaking value-chain, certification, and authenticity bear paramount
significance. Both rely upon the meticulous classification of grapevine varieties on which …

Societal Impact Statement Grapevine leaves are emblematic of the strong visual
associations people make with plants. Leaf shape is immediately recognizable at a glance …

Accurate classification of grapevine leaves is crucial for the advancement of vineyard
industries, as different grapevine varieties require distinct care techniques. However, the …

This research paper introduces a novel methodology that employs Convolutional Neural
Networks (CNNs) and Support Vector Machines (SVMs) to classify grapevine leaf diseases …

Abstract The Eurasian grapevine (\textit {Vitis vinifera L.}) is the most widely grown
horticultural crop in the world and is important for the economy of many countries. In the …

The Eurasian grapevine (Vitis vinifera L.) is the most widely grown horticultural crop in the
world and is important for the economy of many countries. In the wine production chain …

In the proposed study three major issues have been addressed: Firstly, the diversity of
grapevine accessions worldwide and particularly in Armenia, a small country located in the …