| Autor: |
Manthena, Narasimharaju, Gottumukkala, Raju |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2023, Vol. 2655 Issue 1, p1-5, 5p |
| Abstrakt: |
The smart classroom attendance monitoring system is designed based on the Convolutional Neural Network. In this way it looks like a human entrance and exit to laboratories and universities. When a person approaches a surveillance camera near the entrance, his/her face is automatically recognized, and the entry time is saved. Similar to the end, your face is recognized by the embedded surveillance camera of another Convolutional neural network model and the end time is saved. Our method also assists organizations in providing attendance at the percentage of lectures attended during their time. The smart attendance monitoring system is more reliable, and the traditional way of signature or biological donation provides them with the benefits. It is based on a real-time approach and does not consume laboratories; college students and teachers have more time. Students enter the Check that they are properly investigated at the test site and before performing tasks. Sentences and anonymous images are sent to the teacher's smartphone development based on the Internet of Things (IOT) on the Internet when an anonymous student enters the test site, the smart system directly requests the proposed system is fast, accurate, and has a low computational cost. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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