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Zenodo
2026
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| Online-Zugang: | https://doi.org/10.5281/zenodo.19430026 |
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| _version_ | 1866901601373913088 |
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| author | G. Hari Chandana G. Srinivasa Rao |
| author_facet | G. Hari Chandana G. Srinivasa Rao |
| contents | <p><em><span>Infection of plants is a major limitation and a difficult effort. Diseases affecting plants have the potential to harm fruit and foliage, causing the agriculture sector to suffer large financial losses. Infections of plants are primarily evident on the foliage and stems of the plants. Disease categorization and identification by hand takes a lot of effort and requires the participation of professionals. But quickly, this procedure may be aided by the installation of a system that is computerized. An autonomous maladies identification and categorization system is presented by many existing researchers, which can aid those who cultivate banana crops and make a contribution to the nation's economy thanks to advancements in Machine Learning (ML) and Deep Learning (DL) strategies. The principal objective of this work is to conduct a thorough examination of existing works that have used ML and DL approaches in the agricultural sector, specifically concerning the development of banana plants. As a result, it can be useful for upcoming investigators to determine the caliber and nature of prior studies. The researchers looked at issues about banana plantations. Additionally, the researchers have examined the ML-based models that have been put into use, the data- gathering resources, and the thorough outcomes attained for every study.</span></em></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19430026 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | A thorough study of techniques for finding diseases on banana leaves that use machine learning and deep learning G. Hari Chandana G. Srinivasa Rao <p><em><span>Infection of plants is a major limitation and a difficult effort. Diseases affecting plants have the potential to harm fruit and foliage, causing the agriculture sector to suffer large financial losses. Infections of plants are primarily evident on the foliage and stems of the plants. Disease categorization and identification by hand takes a lot of effort and requires the participation of professionals. But quickly, this procedure may be aided by the installation of a system that is computerized. An autonomous maladies identification and categorization system is presented by many existing researchers, which can aid those who cultivate banana crops and make a contribution to the nation's economy thanks to advancements in Machine Learning (ML) and Deep Learning (DL) strategies. The principal objective of this work is to conduct a thorough examination of existing works that have used ML and DL approaches in the agricultural sector, specifically concerning the development of banana plants. As a result, it can be useful for upcoming investigators to determine the caliber and nature of prior studies. The researchers looked at issues about banana plantations. Additionally, the researchers have examined the ML-based models that have been put into use, the data- gathering resources, and the thorough outcomes attained for every study.</span></em></p> |
| title | A thorough study of techniques for finding diseases on banana leaves that use machine learning and deep learning |
| url | https://doi.org/10.5281/zenodo.19430026 |