Výsledky vyhledávání

Cattle Segmentation and Contour Detection Based on Solo for Precision Livestock Husbandry

Autor: Bello, R. W., Ikeremo, E. S., Otobo, F. N., Olubummo, D. A., Enuma, O. C.

Publikováno v: Journal of Applied Sciences and Environmental Management; Vol. 26 No. 10 (2022); 1713-1720

Segmenting objects such as herd of cattle in natural and cluttered images is among the herculean dense prediction tasks of computer vision application to agriculture. To achieve the segmentation goal, we based the segmentation on the model of single

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::77d550c17432b506c95db0ab9858faac
https://doi.org/10.4314/jasem.v26i10.15

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YOLOv7 Applied to Livestock Image Detection and Segmentation Tasks in Cattle Grazing Behavior, Monitor and Intrusions

Autor: Moradeyo, O. M., Olaniyan, A. S., Ojoawo, A. O., Olawale, J. A., Bello, R. W.

Publikováno v: Journal of Applied Sciences and Environmental Management; Vol. 27 No. 5 (2023); 953-958

You only look once (YOLO) is a state-of-the-art, real-time object detection system. YOLO version 7 (YOLOv7) model is a variant of YOLO. The objective of this paper is to apply YOLOv7 to livestock image detection and segmentation tasks in cattle grazi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=78975075580c::b5e848034eeff68561205ef37e61ebe5
https://www.ajol.info/index.php/jasem/article/view/248237

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Application of Machine Learning Identification and Classification of Muturu and Keteku Cattle Species for a Smart Agricultural Practice in Developing Countries such as Nigeria

Autor: Bello, R. W., Ikeremo, E. S., Olubummo, D. A.

Publikováno v: Journal of Applied Sciences and Environmental Management; Vol. 26 No. 7 (2022); 1259-1262

Smart technologies have drastically reshaped the traditional methods of practicing agriculture as witnessed in husbandry. In this paper, a novel application of machine learning identification and classification of Muturu and Keteku cattle species in

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::63e364d69aae4374d1ac6867b72e3927
https://doi.org/10.4314/jasem.v26i7.11

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Akademický článek

Underwater Image Enhancement for Instance Segmentation using Deep Learning Models.

Autor: BELLO, R. W., OLUIGBO, C. U., PEANOCK, I. G., MORADEYO, O. M.

Publikováno v: Journal of Applied Sciences & Environmental Management; 2023, Vol. 27 Issue 2, p242-247, 5p

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Akademický článek

Application of Region-Based Convolutional Neural Network (R-CNN) for Prompt Segmentation between Infected Cucumber Leaves and Healthy Cucumber Leaves.

Autor: BELLO, R. W., ADIPERE, G. F.

Publikováno v: Journal of Applied Sciences & Environmental Management; 2022, Vol. 26 Issue 11, p1791-1797, 7p

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Cattle identification: the history of nose prints approach in brief

Autor: Bello, R W, Olubummo, D A, Seiyaboh, Z, Enuma, O C, Talib, A Z, Mohamed, A S A

Petersen was the first published paper to address cattle biometrics and identification problem by suggesting a permanent cattle identification method based on nose print principles widely accepted today. His major concern was on proper identification

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______2659::bcc85b215725d85cd70deb25b8ce8193
https://zenodo.org/record/4453870

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Development of a Software Package for Cattle Identification in Nigeria

Autor: Bello, R W, Abubakar, S

Publikováno v: Journal of Applied Sciences and Environmental Management; Vol 23, No 10 (2019); 1825-1828

Open grazing or free-range grazing is one of the methods employed by the Nigeria nomadic cattle herders to provide pasture for their cattle. This method of providing pasture for cattle comes with so many challenges among which are cow swapping, owner

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::b0150f05c4a71479cf41171b0496ee8e
https://zenodo.org/record/4453826

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Akademický článek

Computer vision-based techniques for cow object recognition.

Autor: Bello, R W, Mohamed, A S A, Talib, A Z, Olubummo, D A, Enuma, O C

Publikováno v: IOP Conference Series: Earth & Environmental Science; 2021, Vol. 858, p1-9, 9p

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