Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Murindanyi, Sudi"'
The increasing popularity of Artificial Intelligence in recent years has led to a surge in interest in image classification, especially in the agricultural sector. With the help of Computer Vision, Machine Learning, and Deep Learning, the sector has
Externí odkaz:
http://arxiv.org/abs/2408.12426
The advent of Internet of Things (IoT) technology has generated massive interest in voice-controlled smart homes. While many voice-controlled smart home systems are designed to understand and support widely spoken languages like English, speakers of
Externí odkaz:
http://arxiv.org/abs/2405.19343
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
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
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/
http://agritrop.cirad.fr/603453/
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
Autor:
Sanya, Rahman, Nabiryo, Ann Lisa, Tusubira, Jeremy Francis, Murindanyi, Sudi, Katumba, Andrew, Nakatumba-Nabende, Joyce
Publikováno v:
In Data in Brief February 2024 52
Autor:
Sanya R; Department of Adult and Community Education, Makerere University, Kampala, Uganda., Nabiryo AL; Department of Computer Science, Makerere University, Kampala, Uganda., Tusubira JF; Department of Computer Science, Makerere University, Kampala, Uganda., Murindanyi S; Department of Electrical and Computer Engineering, Makerere University, Kampala Uganda., Katumba A; Department of Electrical and Computer Engineering, Makerere University, Kampala Uganda., Nakatumba-Nabende J; Department of Computer Science, Makerere University, Kampala, Uganda.
Publikováno v:
Data in brief [Data Brief] 2023 Dec 14; Vol. 52, pp. 109952. Date of Electronic Publication: 2023 Dec 14 (Print Publication: 2024).