Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (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)
Here's a concise abstract for your Age and Gender Detection project:
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Abstract:
This project focuses on the implementation of an age and gender detection system using deep learning and computer vision techniques. Leveraging pre-trained convolutional neural networks (CNNs) and OpenCV’s deep learning module (cv2.dnn), the system can accurately predict the age group and gender of individuals in real-time using webcam input. The face detection model identifies faces in the video stream, and the extracted face regions are passed through separate networks trained for age and gender classification. The results are then displayed on the screen, providing a user-friendly visualization. This system has potential applications in various fields including retail analytics, security, targeted advertising, and human-computer interaction.
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Let me know if you want it shortened or tailored for a specific audience (e.g., academic report, tech fest, resume).
Keywords:
Age and gender detection, Machine Learning, AI
Cite Article:
"Age and gender detection using multi model integration", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 4, page no.b596-b600, April-2025, Available :http://www.ijrti.org/papers/IJRTI2504174.pdf
Downloads:
000353
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator