Automating attendance management in human resources: A design science approach using computer vision and facial recognition
Haar Cascade is a cost-effective and user-friendly machine learning-based algorithm for detecting objects in images and videos. Unlike Deep Learning algorithms, which typically require significant resources and expensive computing costs, it uses simple image processing techniques like edge detection...
Saved in:
| Main Authors: | Bao-Thien Nguyen-Tat, Minh-Quoc Bui, Vuong M. Ngo |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-11-01
|
| Series: | International Journal of Information Management Data Insights |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667096824000429 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
FACIAL DETECTION IN COMPUTER VISION: BRIDGING GAP BETWEEN CNN, HAAR CASCADE AND MTCNN
by: Nipun Singhal, et al.
Published: (2025-03-01) -
CNN Performance Improvement for Classifying Stunted Facial Images Using Early Stopping Approach
by: Yunidar Yunidar, et al.
Published: (2025-01-01) -
Effortless Student Attendance: A Smart Human-Computer Interactive System Using Real Time Facial Recognition
by: Ahmad S. Lateef, et al.
Published: (2025-02-01) -
Comparative Analysis of MTCNN and Haar Cascades for Face Detection in Images with Variation in Yaw Poses and Facial Occlusions
by: Omer Abdulhaleem Naser, et al.
Published: (2025-03-01) -
Enhancing Attendance Management Through Face Recognition Technology: A Case Study at Rugarama School of Nursing and Midwifery.
by: Taremwa, Benjamin
Published: (2024)