VGG-ICNN: A Lightweight CNN model for crop disease identification

Crop diseases cause a substantial loss in the quantum and quality of agricultural production. Regular monitoring may help in early stage disease detection an d thereby reduction in crop loss. An automatic plant disease identification system based on visual symptoms can provide a smart agriculture so...

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Vydáno v:	Multimedia tools and applications Ročník 82; číslo 1; s. 497 - 520
Hlavní autoři:	Thakur, Poornima Singh, Sheorey, Tanuja, Ojha, Aparajita
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.01.2023 Springer Nature B.V
Témata:	Agricultural production Artificial neural networks Computer Communication Networks Computer Science Crop diseases Data Structures and Information Theory Datasets Deep learning Image processing Lightweight Machine learning Medical imaging Multimedia Information Systems Plant diseases Signs and symptoms Special Purpose and Application-Based Systems Deep learning Crop disease identification Convolutional neural network Classification
ISSN:	1380-7501, 1573-7721
On-line přístup:	Získat plný text
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