Multi-Head Attention-Based Transfer Learning Approach for Potato Disease Detection

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F26%3A0185640" target="_blank" >RIV/00216305:26220/26:0185640 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Multi-Head Attention-Based Transfer Learning Approach for Potato Disease Detection
Original language description
Potatoes are widely consumed all over the world. Being one of the most cultivated crops around the world, they also attract various diseases. Hence, the early identification of such diseases using machine learning-based automated methods, is necessary. In this paper, the solution for the early detection of two most commonly occurring diseases in potato leaves, i.e. Early blight and Late blight have been proposed. In this work, a VGG16 model has been fine-tuned with a multihead attention layer for identifying useful patterns for the classification of potato plant leaf diseases. The multi-head attention mechanism is useful since it can capture the relationship that exists in different parts of an input potato disease leaf image. The proposed model has attained an accuracy of 91% with an F1-score of 0.9103. The better performance of the proposed model is a testimony to its effectiveness in the early identification of potato leaf disease.
Czech name
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Czech description
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Project
<a href="/en/project/CK04000027" target="_blank" >CK04000027: Traffic controll system of new generation (SENDER)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2023 15th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)
ISBN
979-8-3503-9328-6
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
165-169
Publisher name
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Place of publication
Gent
Event location
Gent, Belgium
Event date
Oct 30, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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