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An efficient real-time apple disease classification approach using a novel lightweight neural network on an Arduino edge device
| Title: | An efficient real-time apple disease classification approach using a novel lightweight neural network on an Arduino edge device | Authors: | Grujev, Milan   ; Stojanovic, Dragan ; Milosavljevic, Aleksandar ; Ilic, Milos; Prodanovic, Veljko |
Issue Date: | 2025 | Publication: | Internet of Things | ISSN: | 2542-6605 Internet of Things Search Idenfier |
Type: | Article | Collation: | str. 101833-101833 | DOI: | 10.1016/j.iot.2025.101833 | WoS-ID: | 001631691100001 | Scopus-ID: | 2-s2.0-105024991711 | URI: | https://enauka.gov.rs/handle/123456789/1010293 | Project: | Ministry of Science, Technological Development and Innovation of the Republic of Serbia [451-03-137/2025-03/200102] | Metadata source: | (Preuzeto iz CrossRef-a) Prodanović, Veljko | M-category: | 21aM21a |
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