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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM29900

Smart Attend Insights: A Review

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM29900

Volume:

8 |

4 |

Apr 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

MM

Manoj M

RR

Rishna Ramesh

SG

Sandhra Gopi

FPU

Firoz P U

AAS

Athira A S

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Abstract

The study examines developments in facial recognition technology in fields including online marketing, e- learning, e-therapy, security, and attendance tracking. It highlights the significance of emotional intelligence in human- computer interactions, emphasizing in particular the importance of facial emotions as non-verbal indications in digital settings. It tackles issues with implementing facial recognition in resource-constrained systems by creating a deep learning tool for evaluating patient’s moods during e-therapy sessions. With its automated attendance management system, SmartAttend Insights guarantees accurate recording and encourages consistent attendance with its communication tools and notifications. In addition, deep learning algorithms support collaborative learning environments and analyse academic performance. Overall, the study demonstrates how deep learning may significantly improve student engagement, performance, and accountability in the classroom. SmartAttend Insights is a valuable tool for educators, parents, students, and educational institutions.

KEYWORDS

Facial recognition technology attendance tracking deep learning Automated attendance tracking Student engagement

Cite This Article

Manoj M, Rishna Ramesh, Sandhra Gopi, Firoz P U, Athira A S, "Smart Attend Insights: A Review," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 4, Apr 2024.

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Publication Date

12/31/45383

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Double-Blind Peer Review

Review Rounds: 2

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5

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The authors declare no conflict of interest related to this research work.

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