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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | CNN-based student attendance system |
| Authors Name: | Deepali Mishra , Manu Mishra , Ujjawal Shukla , Akhil Pratap Singh |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_213542
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| Published Paper Id: | IJNRD2402069 |
| Published In: | Volume 9 Issue 2, February-2024 |
| DOI: | |
| Abstract: | The study of human face recognition is one of the advancements in computer vision. The attendance system stores face in a face database by using them as objects to be detected, identified, and recorded as a person's identification. Face recognition of the object faces photographed by the camera is achieved by comparing face image data collected by the camera with face photos that have been saved in the face database. This study's face recognition-based attendance system uses a hybrid feature extraction technique that combines CNN and PCA (Principal Component Analysis). The goal of combining these techniques is to create a feature extraction process that is more precise. This camera's face recognition-based attendance system works incredibly well and efficiently to increase the accuracy of user data. This face recognition-based attendance system uses a camera with high accuracy and very accurate data processing, resulting in a dependable and potent real-time human face identification system. Face recognition is one of the most efficient applications for image processing and plays a crucial part in the technical domain. Identifying a person's face is a current authentication problem, particularly regarding school attendance. The process of identifying students using face bio-statistics based on high-definition monitoring and other computer technologies is known as the "face recognition" attendance system. The goal of this system's creation is to digitize the dated method of taking attendance by calling names and keeping handwritten records. The methods used today to take attendance are laborious and time-consuming. Manually recording attendance allows for easy manipulation of the records. |
| Keywords: | face recognition-based attendance system, hybrid feature extraction, CNN PCA, real-time camera, Computer vision |
| Cite Article: | "CNN-based student attendance system ", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 2, page no.a602-a607, February-2024, Available :http://www.ijnrd.org/papers/IJNRD2402069.pdf |
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| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2402069 Registration ID: 213542 Published In: Volume 9 Issue 2, February-2024 DOI (Digital Object Identifier): Page No: a602-a607 Country: Satna, Madhya Pradesh, India Research Area: Electronics & Communication Engg. Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2402069 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2402069 |
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ISSN: 2456-4184
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