| Autor: |
Agrawal Isha, Hegde Prada, Shetty Pooja, Shingane Priyanka |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
ITM Web of Conferences, Vol 40, p 03043 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2271-2097 |
| DOI: |
10.1051/itmconf/20214003043 |
| Popis: |
Identification of plant disease is tough in agribusiness arena. If it is inaccurate, there occurs a tremendous damage in the production and economical price. Leaf Disease detection requires huge amount of work, knowledge, processing time in plant disease. The most used and edible vegetable all over the world is from cucurbitaceous family. The crops under this family have great economic value in the food industry and its production is done in large scale. This family consists of 965 species. If any of these plants catch disease then there would be a tremendous loss in the production of this field yields. Thus, treating them at early stage is best way to prevent such losses. Hence, Deep Learning Algorithm like CNN can be used to detect the diseases of the plants. The leaves of the plants would be used as primary material for identification of the disease, as they are much more visible on the leaves. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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