dc.contributor.advisor | Richard Vincent E. Misa, MIT | |
dc.contributor.author | Cocoy, Kristian Jay P. | |
dc.contributor.author | Ocio, Mary Kareen Joy B. | |
dc.contributor.author | Baloyo, Aldwin Ray O. | |
dc.date.accessioned | 2025-03-17T12:46:10Z | |
dc.date.available | 2025-03-17T12:46:10Z | |
dc.date.issued | 2022-12 | |
dc.identifier.uri | https://repository.umindanao.edu.ph/handle/20.500.14045/1504 | |
dc.description | In Partial Fulfillment of the Requirements for the Degree Bachelor of Science in Computer Science | en_US |
dc.description | Includes bibliographic references | |
dc.description.abstract | The Philippine culture and livelihood agricultural sector are significant, particularly in rice production. However, rice paddy fields are now under the alert to vanish because of monetary setbacks, along with unguided bad chemical application practices that may result in poor harvest and environmental hazards. To alleviate these problems, countless research has been commenced that birthed precision agriculture. From extensive mechanical machinations to small gadgets like smartphones are utilized to ease farmers' labor. Diseases are a problem for farmers and have persisted for centuries until this generation. Image processing, in particular, has been a trend in detecting rice diseases in the 21st century. The researchers in this study plan to utilize TensorFlow Lite image classification as another method in image processing, along with treatment suggestions and guidance for farmers. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Department of Arts and Sciences Education- Bachelor of Science in Computer Science | en_US |
dc.rights | UM Tagum College LIC | |
dc.subject | Image processing | en_US |
dc.title | Rice paddy disease detection using image processing | en_US |
dc.type | Thesis | en_US |
dc.contributor.panel | Benjamin M. Mahinay Jr., MIT | |
dc.contributor.panel | John Jefferson Dela Cruz, MIT | |
dc.description.xtnt | vi, 21 pages | |