dc.contributor.author | Agora, Paul | |
dc.date.accessioned | 2024-01-19T06:36:17Z | |
dc.date.available | 2024-01-19T06:36:17Z | |
dc.date.issued | 2022-08-18 | |
dc.identifier.citation | Agora, Paul. (2022). An embedded, machine learning-enabled platform for in-field screening of plant disease and pest damage. (Unpublished undergraduate dissertation) Makerere University; Kampala, Uganda. | en_US |
dc.identifier.uri | http://hdl.handle.net/20.500.12281/18316 | |
dc.description | A research report submitted to the College of Engineering Design and Art in partial fulfillment of the requirement for the award of the degree Bachelor of Telecommunications Engineering of Makerere University. | en_US |
dc.description.abstract | This report contains the details of the project that we did for a span of 8 months. Chapter
one covers the project background, problem statement, justification and objectives of
the project Chapter two covers the literature review of the modules we covered and
these include; Machine learning course basics, deep learning, setting up development
environments, making machine learning models and related work Chapter three covers
the practical work including the methodology of the project that we used Finally, chapter
four contains my new findings, challenges, recommendations and conclusions. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Makerere University | en_US |
dc.subject | Machine learning-enabled platform | en_US |
dc.subject | In-field screening of plant disease | en_US |
dc.subject | In-field screening of pest damage | en_US |
dc.title | An embedded, machine learning-enabled platform for in-field screening of plant disease and pest damage | en_US |
dc.type | Thesis | en_US |