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by IQAC KIITKIIT Deemed to be University — Internal Quality Assurance Cell

Publication2023

A computer vision-based perceived attention monitoring technique for smart teaching

The record

Type
Publication
Date
1 March 2023
Level
National
Journal
Multimedia Tools and Applications
Volume
82
Issue
8
Pages
11523-11547
Published
1 March 2023
DOI
10.1007/s11042-022-14283-z
Scopus ID
85144536734
ISSN
13807501
Authors
4
Open access
No
Citations
11
International co-authorship
No
Co-author countries
IN

Classification

Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.

UN Sustainable Development Goals

  1. 4.4 Substantially increase the number of youth and adults with relevant skills for employment, decent jobs and entrepreneurship

    TargetPrimaryHigh confidenceJudged

    Computer vision system monitoring student attention using deep learning enables real-time pedagogical adaptation in physical and remote classrooms, directly supporting development of digital competencies and learning skills.

    High confidence
    The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
    Judged
    Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

Viksit Bharat @2047

  1. vb-1.1 Education and lifelong learning

    Sub-themePrimaryHigh confidenceJudged

    Deep learning-based attention detection in smart teaching environments (outperforming ResNet50 and MobileNetV2) enhances lifelong learning through personalized educational feedback mechanisms.

    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

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KIIT Deemed to be University. “A computer vision-based perceived attention monitoring technique for smart teaching”. Kortex.

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