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- W4313444479 abstract "The paper aims to recognize and identify two types of fungi affected leaves, insect eaten leaf and healthy leaves of Guava (Psidium Guajava) plant, as most of the crops are lost to fungi. The aim is to work on the prime crop of our H&K (Hyderabad & Karnataka) region, which will help the farmers of this region as there is no work done on this crop. The dataset is possessed from a fruit-farm of H&K region of Karnataka, India. We have implemented both Machine learning (ML) and Deep learning (DL) techniques to get good results on the collected real time environment dataset. We eliminate the preprocessing step to reduce the time complexity. The performance measures obtained from the experiments shows that the Deep learning model performed well as compared to the ML techniques." @default.
- W4313444479 created "2023-01-06" @default.
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- W4313444479 date "2023-01-01" @default.
- W4313444479 modified "2023-09-27" @default.
- W4313444479 title "Classification of Fungi Effected Psidium Guajava Leaves Using ML and DL Techniques" @default.
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- W4313444479 doi "https://doi.org/10.1007/978-981-19-7169-3_7" @default.
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