Smart attendance using deep learning and computer vision

被引:5
|
作者
Seelam, Vivek [1 ]
Penugonda, Akhil Kumar [1 ]
Kalyan, B. Pavan [1 ]
Priya, M. Bindu [1 ]
Prakash, M. Durga [1 ]
机构
[1] Velagapudi Ramakrishna Siddhartha Engn Coll, Dept Elect & Commun Engn, Vijayawada 520007, Andhra Pradesh, India
关键词
Convolutional Neural networks; Deep learning; Facenet; Haar cascades; Raspberry Pi; Smart classroom;
D O I
10.1016/j.matpr.2021.02.625
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Attendance is an essential part of daily classroom evaluation. Traditional classroom follows a manual attendance marking system, i.e., calling a student's names or by forwarding an attendance sheet. This process is both time-consuming and error-prone, i.e., student proxy, etc. Hence a face recognition based smart classroom attendance management system using computer vision and deep learning implemented on a Raspberry Pi has been proposed. It has been proposed to mount a camera at the top of the blackboard so that the students are visible while they are sitting down. A face detection algorithm followed by face recognition has been used to mark the attendance of the detected student. (c) 2020 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Conference on Materials, Manufacturing and Mechanical Engineering for Sustainable Developments-2020.
引用
收藏
页码:4091 / 4094
页数:4
相关论文
共 50 条
  • [21] American Sign Language Recognition using Deep Learning and Computer Vision
    Bantupalli, Kshitij
    Xie, Ying
    2018 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2018, : 4896 - 4899
  • [22] Construction Site Hazards Identification Using Deep Learning and Computer Vision
    Alateeq, Muneerah M.
    Fathimathul Rajeena, P. P.
    Ali, Mona A. S.
    SUSTAINABILITY, 2023, 15 (03)
  • [23] Detection of Safety Signs Using Computer Vision Based on Deep Learning
    Wang, Yaohan
    Song, Zeyang
    Zhang, Lidong
    APPLIED SCIENCES-BASEL, 2024, 14 (06):
  • [24] Automated Borehole Image Interpretation Using Computer Vision and Deep Learning
    Gharieb, Amr
    Ibrahim, Ahmed Farid
    Gabry, Mohamed Adel
    Elsawy, Mohamed
    Algarhy, Ahmed
    Darraj, Nihal
    SPE JOURNAL, 2024, 29 (12): : 6918 - 6933
  • [25] Recognition of Cough on Sequence Images Using Deep Learning and Computer Vision
    Quispe Siancas, Nadia L.
    Monroy Barrios, Jhon E.
    Nina Choquehuayta, Wilder
    INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 3, INTELLISYS 2024, 2024, 1067 : 382 - 394
  • [26] Vehicle Speed Estimation and Tracking Using Deep Learning and Computer Vision
    Sathyabama, B.
    Devpura, Ashutosh
    Maroti, Mayank
    Rajput, Rishabh Singh
    INNOVATIVE DATA COMMUNICATION TECHNOLOGIES AND APPLICATION, ICIDCA 2021, 2022, 96 : 77 - 88
  • [27] Real Time Weed Detection using Computer Vision and Deep Learning
    Junior, Luiz Carlos M.
    Ulson, Jose Alfredo C.
    2021 14TH IEEE INTERNATIONAL CONFERENCE ON INDUSTRY APPLICATIONS (INDUSCON), 2021, : 1131 - 1137
  • [28] Human Action Recognition using Computer Vision and Deep Learning Techniques
    Ganta, Suresh
    Desu, Devi Sri
    Golla, Aishwarya
    Kumar, M. Ashok
    2023 ADVANCED COMPUTING AND COMMUNICATION TECHNOLOGIES FOR HIGH PERFORMANCE APPLICATIONS, ACCTHPA, 2023,
  • [29] Strawberry plant wetness detection using computer vision and deep learning
    Patel, Arth
    Lee, Won Suk
    Peres, Natalia A.
    Fraisse, Clyde W.
    SMART AGRICULTURAL TECHNOLOGY, 2021, 1
  • [30] Special focus on deep learning for computer vision
    Pang, Yanwei
    Bai, Xiang
    Zhang, Guofeng
    SCIENCE CHINA-INFORMATION SCIENCES, 2019, 62 (12)