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    Mobile-Based convolutional neural network model for the early identification of banana diseases 

    Elinisa, Christian; Mduma, Neema (Elsevier, 2024-02-29)
    This study aimed to deploy a deep learning model in a mobile application for the early identification of Fusarium Wilt and Black Sigatoka in bananas. In this paper, a Convolutional Neural Network (CNN) model for the ...
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    Feature Selection Approach to Improve Malaria Prediction Model’s Performance for High- and Low-Endemic Areas of Tanzania 

    Mariki, Martina; Mduma, Neema; Mkoba, Elizabeth (Springer Link, 2024-06)
    Malaria remains a significant cause of death, especially in sub-Saharan Africa, with about 228 million malaria cases worldwide. Parasitological tests, like microscopic and rapid diagnostic tests (RDT), are the recommended ...
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    Mobile-Based convolutional neural network model for the early identification of banana diseases 

    Elinisa, Christian; Mduma, Neema (Elsevier, 2024-02-29)
    This study aimed to deploy a deep learning model in a mobile application for the early identification of Fusarium Wilt and Black Sigatoka in bananas. In this paper, a Convolutional Neural Network (CNN) model for the ...
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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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    Author
    Mduma, Neema (11)
    Elinisa, Christian (4)Mayo, Flavia (3)Maina, Ciira (2)Bainomugisha, Engineer (1)Bradshaw, Karen (1)Irungu, Annette (1)Kaijage, Shubi (1)Kihoza, Patrick (1)Kimei, Erica (1)... View MoreSubjectBlack sigatoka (2)Classification (2)Convolutional neural network (2)Deep learning (2)Fusarium wilt (2)Mobile application (2)TECHNOLOGY (2)carbon dioxide (1)convolutional neural network (1)deep learning models (1)... View MoreDate Issued
    2024 (11)
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