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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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Issue: May 2024
Volume 9 | Issue 5
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| Paper Title: | Age and Gender detection using python |
| Authors Name: | Aruna Devi.M , Sakthi Poojitha.M , Sahayariyasha.V , Shenbagam.E |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_219676
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| Published Paper Id: | IJNRD2404769 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| Abstract: | This project revolves around age and gender detection through machine learning, finding applications in diverse fields like marketing, social research, and security. Leveraging Python's advancements, including TensorFlow, OpenCV, PyTorch, Keras, and scikit-learn, enhances code efficiency. By analyzing wrinkles, facial features, and other factors, it accurately discerns age, gender, and even religion from scanned images. Data collection involves over 10,000 labeled images extracted through Excel and CSV formats, contributing to model training. Preprocessing techniques like resizing, augmentation, and normalization enhance dataset quality and diversity. Feature extraction captures vital image characteristics, crucial for accurate detection. Pre-trained data models further refine efficiency and accuracy. Real-time applications in security and surveillance underscore its practical relevance. However, challenges such as facial feature variations require meticulous handling. Ethical considerations, including privacy safeguards and fair demographic analysis, are integral. Overall, this project merges image processing, machine learning, and data analysis, promising automated demographic attribute identification from visual content, with broad implications across industries. |
| Keywords: | OpenCV, Age estimation, Gender classification, TensorFlow, PyTorch, Feature extraction, Fine-tuning, Evaluation metrics, Accuracy analysis |
| Cite Article: | "Age and Gender detection using python", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.h661-h670, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404769.pdf |
| Downloads: | 00027 |
| 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:IJNRD2404769 Registration ID: 219676 Published In: Volume 9 Issue 4, April-2024 DOI (Digital Object Identifier): Page No: h661-h670 Country: Tirunelveli, Tamil Nadu, India Research Area: Information Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2404769 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2404769 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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