A disease recognition method based on deep learning is proposed. This paper has improved the pre-selected box setting formula of the SSD model and tested it in multiple SSD models. Experiments show that the average accuracy of the final SSD768 model is 92.4%, and the average accuracy of the IOU is 88.9%.
This paper has improved the pre-selected box setting formula of the SSD model and tested it in multiple SSD models, showing that this method can be used to ...
Mar 27, 2021 · In this paper, the healthy leaves, leaves with spot disease, leaves with blight and anthracnose-a®ected leaves of watermelon were collected from ...
This paper presents a large dataset of watermelons that can be used to train a machine vision-based illness detection model.
Blazquez and Edwards (1986) developed a laboratory-based technique to detect watermelon infected with Fusarium wilt, downy mildew, and watermelon mosaic. ...
Oct 15, 2020 · A disease recognition method based on deep learning is proposed. This paper has improved the pre-selected box setting formula of the SSD model ...
Feb 13, 2024 · This paper presents a large dataset of watermelons that can be used to train a machine vision-based illness detection model.
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We present a unique strategy for the precise identification of watermelon disease of the leaves using a model of deep learning in this study.
Borhani et al. (2022) developed a deep learning-based method for automated plant disease categorization utilizing a vision transformer in order to give farmers ...
This paper exhibits the correlations between Watermelon yield and proposed disease prediction indices in the Indian largest Watermelon-exporting form. Only ...