International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Student Management with Face Recognition System |
|---|---|
| ABSTRACT | Managing student records, attendance, and access control efficiently is a core requirement for modern educational institutions. This paper presents the design and implementation of a Student Management System (SMS) that integrates face recognition to automate attendance marking, secure access, and streamline student data management. The proposed system combines image acquisition, face detection, feature extraction, and classification modules to identify students in real time, update attendance logs, and provide administrative interfaces for record management. We evaluate the system using commonly used face recognition techniques (LBPH, Eigenfaces, Fisherfaces, and deep-learning-based embeddings) and discuss trade-offs in accuracy, speed, and deployability. The results show that a hybrid approach—using lightweight local models for real-time capture and cloud or server-side deep embeddings for periodic revalidation—offers a good balance between performance and resource usage. Finally, we discuss integration with existing student information systems, privacy considerations, and directions for future work. |
| TITLE | |
| AUTHOR | ABHIRAJE NIMBALKAR, YASH CHAUDHARI, AKSHADA BAMDALE, KARTIK PAWAR, SHREYASH KOLTE, PROF. NAMDEV KEDARE |
| PUBLICATION DATE | 2025-11-01 |
| VOLUME | 175 |
| DOI | DOI: 10.15680/IJIRCCE.2025.1310028 |
| pdf/28_Student Management with Face Recognition System.pdf | |
| KEYWORDS |
