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- W4312101855 abstract "In the context of the STEM approach to education, motivating pupils through tailored research and leveraging IT in the classroom is relevant. The justification of these approaches hasn't received much examination, though. The purpose of the study is to support the decision to use an AR-plant recognition application to give tailored instruction throughout both extracurricular activities and the school day. Every phase of an app's interaction with a user was examined and used to categorize every app. Also described were the social settings of the applications and how they were used for extracurricular activities. There has been discussion on the didactics of using AR recognition apps in biology classes. A survey of experts in digital education regarding the ease of installation, the friendliness of the interface, and the accuracy of image processing was conducted to give usability analysis. Applications were examined for their ability to accurately identify plants on the Dneprovskiy district of Kiev list in order to assess the rationale of usage. It has been established that Google Lens is the best option. As an alternative to Seek or Flora Incognita, according to the analysis's findings, these apps were less accurate." @default.
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- W4312101855 date "2022-12-21" @default.
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- W4312101855 title "Comparison of Google Lens recognition performance with other plant recognition systems" @default.
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- W4312101855 doi "https://doi.org/10.55056/etq.433" @default.
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