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- W4311372488 abstract "AbstractIn the age of industrial revolution 4.0, there are more and more technology applications used in agriculture. As such, smart agriculture has become a trend of this development, especially in diagnosing plant diseases and suggesting corresponding treatment methods. Although many works have been conducted to predict plant disease based on visual information, the number of works for end-to-end recommendation systems about the treatment of plant diseases has been limited. The main reason is the requirement of a dataset with plant disease images and corresponding treatment descriptions respectively. In this paper, to address this issue, we firstly extended the CrowdAI disease dataset by increasing plant disease labels as well as collecting treatment descriptions for each plant disease class. Secondly, we propose an end-to-end recommendation system for treating plant diseases, including the diagnosing of plant diseases based on images and then recommending efficient treatment based on cross-modal data. Finally, we have developed a web-based application for recommending plant disease treatments.KeywordsPlant diseasesRecommendation systemConvolutional neural network" @default.
- W4311372488 created "2022-12-25" @default.
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- W4311372488 date "2022-12-15" @default.
- W4311372488 modified "2023-10-16" @default.
- W4311372488 title "An Automatic Recommendation System for Plant Disease Treatment" @default.
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- W4311372488 doi "https://doi.org/10.1007/978-3-031-19694-2_55" @default.
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