Performance Evaluation of VegeCare Tool for Tomato Disease Classification

Ruedeeniraman, Natwadee; Ikeda, Makoto; Barolli, Leonard

doi:10.1007/978-3-030-29029-0_59

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2020

2023

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Cited by 4 publications

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“…For the next generation of farmers, the intelligent growth management system is important for increasing crops' productivity [2,6]. In [17,18], we proposed a classification system considering potato and tomato diseases. We analyzed the classification performance in two of four major crop types as tubers, fruits, cereals and pulses.…”

Section: Introductionmentioning

confidence: 99%

An Intelligent VegeCare Tool for Corn Disease Classification

Ruedeeniraman

Ikeda

Barolli

2020

Advances on P2P, Parallel, Grid, Cloud and Internet Computing

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Due to the decrease of the agricultural population, agriculture has widely applied to machine learning and deep learning. In this paper, we present the classification performance of the proposed VegeCare tool for corn disease classification. We classify the major leaf diseases of the corn crop. The dataset includes four classes: gray leaf spot, common rust, health and northern leaf blight. From this evaluation, we found that our proposed VegeCare tool has a good performance.

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