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A novel deep CNN model with entropy coded sine cosine for corn disease classification

Crossref DOI link: https://doi.org/10.1016/j.jksuci.2024.102126

Published Print: 2024-09

Update policy: https://doi.org/10.1016/elsevier_cm_policy

Authors

Malik, Mehak Mushtaq https://orcid.org/0009-0007-3418-9832
Fayyaz, Abdul Muiz

Yasmin, Mussarat

Abdulkadir, Said Jadid https://orcid.org/0000-0003-0038-3702
Al-Selwi, Safwan Mahmood https://orcid.org/0009-0000-2742-213X
Raza, Mudassar https://orcid.org/0000-0001-9124-9298
Waheed, Sadia
Funding

Funding for this research was provided by:

Yayasan Universiti Teknologi PETRONAS (YUTP-FRG/015LC0-521)

Universiti Teknologi Petronas

Malaysia Ministry of Higher Education (FRGS/1/2022/ICT02/UTP/02/4)
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Text and Data Mining valid from 2024-09-01

Text and Data Mining valid from 2024-09-01

Version of Record valid from 2024-07-09
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This article is maintained by: Elsevier

Article Title: A novel deep CNN model with entropy coded sine cosine for corn disease classification

Journal Title: Journal of King Saud University - Computer and Information Sciences

CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.jksuci.2024.102126

Content Type: article

Copyright: © 2024 The Author(s). Published by Elsevier B.V. on behalf of King Saud University.