Zobrazeno 1 - 10 of 30 pro vyhledávání: '"Rotimi-Williams Bello"'
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Akademický článek
Photovoltaic module dataset for automated fault detection and analysis in large photovoltaic systems using photovoltaic module fault detectionMendeley Data
Autor: Rotimi-Williams Bello, Pius A. Owolawi, Etienne A. van Wyk, Chunling Du
Publikováno v: Data in Brief, Vol 57, Iss , Pp 111184- (2024)
Solar energy has become the fastest growing renewable and alternative source of energy. However, there is little or no open-source datasets to advance research knowledge in photovoltaic related systems. The work presented in this article is a step to
Externí odkaz: https://doaj.org/article/2f480e2d101f40279f509e91ecbb8164
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2
Akademický článek
Contour Extraction of Individual Cattle From an Image Using Enhanced Mask R-CNN Instance Segmentation Method
Autor: Rotimi-Williams Bello, Ahmad Sufril Azlan Mohamed, Abdullah Zawawi Talib
Publikováno v: IEEE Access, Vol 9, Pp 56984-57000 (2021)
In animal husbandry, the traceability of individual cattle, their health information, and performance records greatly depend on computer vision and image processing-based approaches. However, some of these approaches perform below expectations in obt
Externí odkaz: https://doaj.org/article/b60c4c9db39040bb9f9456b260d69085
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5
A Precision Agricultural Application: Manggis Fruit Classification Using Hybrid Deep Learning
Autor: Nur Anis Liyana, Wan Muhammad Azimuddin Wan Ahmad, Rotimi-Williams Bello, Abdullah Zawawi Talib, Putra Sumari, Faris Hadi, Muhammad Mazlan, Ahmad Sufril Azlan Mohamed
Publikováno v: Revue d'Intelligence Artificielle. 35:375-381
Fruits come in different variants and subspecies. While some subspecies of fruits can be easily differentiated, others may require an expertness to differentiate them. Although farmers rely on the traditional methods to identify and classify fruit ty
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::eddbe64ad2c2a0a62eba31f84061ffdc
https://doi.org/10.18280/ria.350503
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6
Contour Extraction of Individual Cattle From an Image Using Enhanced Mask R-CNN Instance Segmentation Method
Autor: Ahmad Sufril Azlan Mohamed, Abdullah Zawawi Talib, Rotimi-Williams Bello
Publikováno v: IEEE Access, Vol 9, Pp 56984-57000 (2021)
In animal husbandry, the traceability of individual cattle, their health information, and performance records greatly depend on computer vision and image processing-based approaches. However, some of these approaches perform below expectations in obt
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aa8c9da06d9650be1912a27895cd87d3
https://ieeexplore.ieee.org/document/9400819/
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