Výsledky vyhledávání - "Mutegeki, Henry"

Akademický článek

The Ugandan sickle Pan-African research consortium registry: design, development, and lessons.

Autor: Nsubuga, Mike^1,2,3,4 (AUTHOR), Mutegeki, Henry^3,4,5 (AUTHOR), Jjingo, Daudi^3,4,5 (AUTHOR), Munube, Deogratias⁶ (AUTHOR), Namazzi, Ruth⁶ (AUTHOR), Opoka, Robert^6,7,8 (AUTHOR), Kasirye, Philip⁶ (AUTHOR), Ndeezi, Grace⁶ (AUTHOR), Hume, Heather⁹ (AUTHOR), Mupere, Ezekiel⁶ (AUTHOR), Kebirungi, Grace^3,4 (AUTHOR), Birungi, Isaac⁸ (AUTHOR), Morrice, Jack¹⁰ (AUTHOR), Jonas, Mario¹⁰ (AUTHOR), Nembaware, Victoria¹⁰ (AUTHOR), Wonkam, Ambroise¹¹ (AUTHOR), Makani, Julie¹² (AUTHOR), Kiguli, Sarah⁶ (AUTHOR) skwalube@yahoo.co.uk

Publikováno v: BMC Medical Informatics & Decision Making. 7/29/2024, Vol. 24 Issue 1, p1-8. 8p.

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Akademický článek

Using machine learning for image-based analysis of sweetpotato root sensory attributes

Autor: Nakatumba-Nabende, Joyce, Babirye, Claire, Tusubira, Jeremy Francis, Mutegeki, Henry, Nabiryo, Ann Lisa, Murindanyi, Sudi, Katumba, Andrew, Nantongo, Judith, Sserunkuma, Edwin, Nakitto, Mariam, Ssali, Reuben, Makunde, Godwill, Moyo, Mukani, Campos, Hugo

Publikováno v: In Smart Agricultural Technology October 2023 5

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Standard operating procedure for image capture in sweetpotato and potato, and sensory attribute prediction. Work package 3

Autor: Nakatumba-Nabende, Joyce, Katumba, Andrew, Murindanyi, Sudi, Nabiryo, Ann Lisa, Babirye, Claire, Tusubira, Jeremy Francis, Mutegeki, Henry, Nantongo, Judith S, Sserunkuma, Edwin, Ssali, Reuben

The applications of computer vision technology for acquiring and analysing images have been extended to the evaluation of important crop traits for enhancing breeding programmes. Imaging technology is a fast, non-destructive high-throughput phenotypi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::322b6e99072b01c63983bab4ca2f0964

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Predicting sweetpotato sensory attributes using image analysis. DigiEye and image analysis as a breeding tool

Autor: Nakatumba-Nabende, Joyce, Nabiryo, Ann Lisa, Babirye, Claire, Tusubira, Jeremy Francis, Katumba, Andrew, Murindanyi, Sudi, Mutegeki, Henry, Nantongo, Judith S, Sserunkuma, Edwin, Nakitto, Mariam, Ssali, Reuben

The objective of the work was to develop, test and evaluate a color and mealiness classification model based on images of sweetpotato roots. A total of 3018 images were collected from 950 samples from October 2021 to November 2022. The captured image

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______3631::0f8d9505494ba4cf77642c919841a9cd
http://agritrop.cirad.fr/603453/

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Standard Operating Procedure for DigiEye calibration. Work package 3

Autor: Nakatumba-Nabende, Joyce, Katumba, Andrew, Murindanyi, Sudi, Nabiryo, Ann Lisa, Babirye, Claire, Tusubira, Jeremy Francis, Mutegeki, Henry, Nantongo, Judith S, Nakitto, Mariam, Sserunkuma, Edwin, Ssali, Reuben

A variety of imaging sensors are currently used in research and commercial practices to quantify complex crop traits for breeders. Imaging technology is a fast, non-destructive high-throughput phenotyping tool that has been used widely for accurate a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3ec13a048f736ae095daa2e9bf7bf719

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