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    Now showing items 11-20 of 33

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    Computer Science Education in Selected Countries from Sub-Saharan Africa 

    Bainomugisha, Engineer; Bradshaw, Karen; Ujakpa, Martin; Nakatumba-Nabende, Joyce; Nderu, Lawrence; Mduma, Neema; Kihoza, Patrick; Irungu, Annette (ACM Inroads, 2024-02-20)
    Computer Science education in sub-Saharan Africa has evolved over the past decades. The number of institutions offering distinct undergraduate programs has grown, thus increasing the number of students enrolling in the ...
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    Updating “machine learning imagery dataset for maize crop: A case of Tanzania” with expanded data to cover the new farming season 

    Mduma, Neema; Mayo, Flavia (Elsevier Inc., 2024-03-23)
    Maize Lethal Necrosis (MLN) and Maize Streak Virus (MSV) are among maize diseases which affect productivity in Tan- zania and Africa at large. These diseases can be detected early for timely interventions and minimal ...
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    Image Segmentation Deep Learning Model for Early Detection of Banana Diseases 

    Elinisa, Christian; Maina, Ciira; Vodacek, Anthony; Mduma, Neema (Taylor & Francis online, 2024-12-14)
    Bananas are among the most widely produced perennial fruits and staple food crops that are highly affected by numerous diseases. When not managed early, Fusarium Wilt and Black Sigatoka are two of the most detrimental ...
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    Deep learning models for the early detection of maize streak virus and maize lethal necrosis diseases in Tanzania 

    Mduma, Neema; Mgala, Mvurya; Maina, Ciira; Mayo, Flavia (International Journal of Innovative Research & Development, 2024-08-16)
    Agriculture is considered the backbone of Tanzania’s economy, with more than 60% of the residents depending on it for survival. Maize is the country’s dominant and primary food crop, accounting for 45% of all farmland ...
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    The Artificial Neural Network-Based Smart Number Plate for Vehicles with Real-Time Traffic Signs Recognition and Notification 

    Niyomugaba, Alexandre; Kisangiri, Michael; Mduma, Neema (Springer Link, 2024-06-30)
    The world is advancing technologically in all sectors, including intelligent transportation, whereby various vehicles’ movements are monitored and controlled remotely. These technologies simplify the tasks in traffic control ...
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    Convolutional Neural Network Deep Learning Model for Early Detection of Streak Virus and Lethal Necrosis in Maize: A Case of Northern-Highlands, Tanzania 

    Mayo, Flavia; Mduma, Neema (Springer Link, 2024-06-30)
    In the Tanzanian context, maize is the dominant food crop that serves as a significant common and traditional food being grown in about 45% of the country’s farmland. However, its productivity is hindered by diseases that ...
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    Mask R-CNN Model for Banana Diseases Segmentation 

    Elinisa, Christian; Mduma, Neema (Springer Link, 2024)
    Early detection of banana diseases is necessary for developing an effective control plan and minimizing quality and financial losses. Fusarium Wilt Race 1 and Black Sigatoka diseases are among the most harmful banana ...
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    A Machine Learning Model for detecting Covid-19 Misinformation in Swahili Language 

    Mlawa, Filbert; Mkoba, Elizabeth; Mduma, Neema (Engineering, Technology & Applied Science Research, 2023-06-02)
    The recorded cases of corona virus (COVID-19) pandemic disease are millions and its mortality rate was maximized during the period from April 2020 to January 2022. Misinformation arose regarding this threat, which spread ...
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    Machine learning model for predicting Peste des Petits Ruminants 

    Nyambo, Devotha; Ngulumbi, Nguse; Mduma, Neema; Sinde, Ramadhani; Lyimo, Tumaini (IEEE, 2023-11-16)
    Peste des petits ruminants (PPR) is a viral disease that affects small ruminants and is prevalent in many developing countries, particularly in Africa and Asia. It can spread through direct contact, air, and contaminated ...
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    Banana Leaves Imagery Dataset 

    Mduma, Neema; Elinisa, Christian (Springer Nature, 2025-03-21)
    In this work, we present a dataset of banana leaf imagery, both with and without diseases. The dataset consists of 11,767 images, categorized as follows: 3,339 healthy images, 3,496 images of leaves affected by Black ...
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    Mduma, Neema (33)
    Elinisa, Christian (5)Kalegele, Khamisi (5)Machuve, Dina (5)Mkoba, Elizabeth (4)Nyambo, Devotha (4)Dida, Mussa (3)Mariki, Martina (3)Mayo, Flavia (3)Sinde, Ramadhani (3)... View MoreSubjectDeep learning (4)TECHNOLOGY (4)machine learning (3)Mobile application (3)Black sigatoka (2)Classification (2)Convolutional neural network (2)Fusarium wilt (2)Imbalanced learning classification (2)Machine learning (2)... View MoreDate Issued2024 (11)2023 (8)2021 (4)2019 (3)2022 (3)2025 (2)2015 (1)2017 (1)Has File(s)
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