Ringworm Detection and Diagnosis System.
Ringworm, a common fungal infection, affects millions worldwide. Early detection is crucial for effective treatment and prevention of transmission. This report presents a novel ringworm detection system utilizing deep learning and image processing. We carried out our research within a period of seve...
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| Main Authors: | , |
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| Format: | Thesis |
| Language: | English |
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Kabale University
2024
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| Online Access: | http://hdl.handle.net/20.500.12493/2582 |
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| _version_ | 1823844185259638784 |
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| author | Asiimwe, Joab Barigye, Deus Dedet |
| author_facet | Asiimwe, Joab Barigye, Deus Dedet |
| author_sort | Asiimwe, Joab |
| collection | KAB-DR |
| description | Ringworm, a common fungal infection, affects millions worldwide. Early detection is crucial for effective treatment and prevention of transmission. This report presents a novel ringworm detection system utilizing deep learning and image processing. We carried out our research within a period of seven months and our system performed the desired work. We developed a ringworm detection and diagnosis system that offers rapid and accurate results for early intervention and treatment. Hardware and software. The system employs picture imaging using processor Intel i5, 8GB RAM, and the operating system Windows 10 Pro. The proposed system achieves an accurate detection rate of ringworm. Sampling method was used like Interviewing and Observation. |
| format | Thesis |
| id | oai:idr.kab.ac.ug:20.500.12493-2582 |
| institution | KAB-DR |
| language | English |
| publishDate | 2024 |
| publisher | Kabale University |
| record_format | dspace |
| spelling | oai:idr.kab.ac.ug:20.500.12493-25822024-12-30T00:01:58Z Ringworm Detection and Diagnosis System. Asiimwe, Joab Barigye, Deus Dedet Ringworm Detection Diagnosis System Ringworm, a common fungal infection, affects millions worldwide. Early detection is crucial for effective treatment and prevention of transmission. This report presents a novel ringworm detection system utilizing deep learning and image processing. We carried out our research within a period of seven months and our system performed the desired work. We developed a ringworm detection and diagnosis system that offers rapid and accurate results for early intervention and treatment. Hardware and software. The system employs picture imaging using processor Intel i5, 8GB RAM, and the operating system Windows 10 Pro. The proposed system achieves an accurate detection rate of ringworm. Sampling method was used like Interviewing and Observation. 2024-12-29T12:06:45Z 2024-12-29T12:06:45Z 2024 Thesis Asiimwe, J., & Barigye, D. D. (2024). Ringworm Detection and Diagnosis System. Kabale: Kabale University. http://hdl.handle.net/20.500.12493/2582 en Attribution-NonCommercial-NoDerivs 3.0 United States http://creativecommons.org/licenses/by-nc-nd/3.0/us/ application/pdf Kabale University |
| spellingShingle | Ringworm Detection Diagnosis System Asiimwe, Joab Barigye, Deus Dedet Ringworm Detection and Diagnosis System. |
| title | Ringworm Detection and Diagnosis System. |
| title_full | Ringworm Detection and Diagnosis System. |
| title_fullStr | Ringworm Detection and Diagnosis System. |
| title_full_unstemmed | Ringworm Detection and Diagnosis System. |
| title_short | Ringworm Detection and Diagnosis System. |
| title_sort | ringworm detection and diagnosis system |
| topic | Ringworm Detection Diagnosis System |
| url | http://hdl.handle.net/20.500.12493/2582 |
| work_keys_str_mv | AT asiimwejoab ringwormdetectionanddiagnosissystem AT barigyedeusdedet ringwormdetectionanddiagnosissystem |