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Online ISSN : 2338-5502
Print ISSN : 2337-5779
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Comparison Study of Corn Leaf Disease Detection based on Deep Learning YOLO-v5 and YOLO-v8

DOI : 10.5614/j.eng.technol.sci.2024.56.1.5
Nidya Chitraningrum (1), Lies Banowati (2), Dina Herdiana (3), Budi Mulyati (4), Indra Sakti (5), Ahmad Fudholi (6), Huzair Saputra (7), Salman Farishi (8), Kahlil Muchtar (9), Agus Andria (10)
(1) Research Center for Biomass and Bioproducts, National Research and Innovation Agency (BRIN), Jalan Raya Jakarta-Bogor No. KM 46, Cibinong, Bogor 16911, Indonesia, Indonesia ,
(2) Department of Aeronatics Engineering, Universitas Nurtanio, Jalan Pajajaran No. 219, Bandung 40174, Indonesia, Indonesia ,
(3) Department of Electrical Engineering, Universitas Nurtanio, Jalan Pajajaran No. 219, Bandung 40174, Indonesia, Indonesia ,
(4) Department of Aeronatics Engineering, Universitas Nurtanio, Jalan Pajajaran No. 219, Bandung 40174, Indonesia, Indonesia ,
(5) Research Center for Telecommunication, National Research and Innovation Agency (BRIN), Jalan Sangkuriang, Kawasan KST Samaun Samadikun Gd. 20, Bandung 40135, Indonesia, Indonesia ,
(6) Research Center for Energy Conversion and Conservation, National Research and Innovation Agency (BRIN), Kawasan PUSPIPTEK, Kluster Energi Gd. 620-625, Setu – Tangerang Selatan 15314, Indonesia, Indonesia ,
(7) Master of Artificial Intelligence, Department of Informatics, Universitas Syiah Kuala, Jalan Syech Abdurrauf No. 3, Kopelma Darussalam, Banda Aceh 23111, Indonesia, Indonesia ,
(8) Research Center for Polymer Technology, National Research and Innovation Agency (BRIN), Kawasan PUSPIPTEK, Gd. 460, Setu – Tangerang Selatan 15314, Indonesia, Indonesia ,
(9) Telematics Research Center (TRC), Universitas Syiah Kuala, Jalan Syech Abdurrauf No. 3, Kopelma Darussalam, Banda Aceh 23111 Banda Aceh, Indonesia, Indonesia ,
(10) The Central Bureau of Statistics (BPS) Kabupaten Simeulue, Jalan Tgk. Diujung Desa Air Dingin, Sinabang, Simelue Timur, Simeulue Regency, Aceh 24782, Indonesia, Indonesia
61-70
Abstract : 6656
PDF : 980
DOI : 10.5614/j.eng.technol.sci.2024.56.1.5
DOI: https://doi.org/10.5614/j.eng.technol.sci.2024.56.1.5
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