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Paper Title

AGE AND GENDER CLASSIFICATION USING DEEP LEARNING WITH IMAGES

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Registration ID: IJNRD_222727

Published ID: IJNRD2405764

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Keywords

Age Classification, Gender Reorganization, Convolutional Neural Networks (CNN), Computer Vision

Abstract

Real-time age and gender detection from facial photos has received substantial interest in today's era of advanced computer vision and deep learning due to its wide range of applications, ranging from tailored user experiences to security systems. Using Convolutional Neural Networks (CNNs), this study proposes a robust and efficient framework for real-time age and gender recognition. To extract discriminative features from input facial photos, our proposed approach employs cutting-edge CNN architectures that have been pretrained on large-scale facial datasets. The network learns hierarchical representations that are critical for age and gender estimation using a combination of convolutional and pooling layers. Unlike older methods that need human feature engineering, our CNN-based solution learns and adapts to the subtle changes in facial photos. We optimize our model for speed and accuracy, employing approaches such as model quantization and efficient network designs, to assure real-time performance. We also build the system on hardware accelerators, which allows it to be deployed on edge devices and real-time video streams. Furthermore, our system performs in real time on ordinary hardware, making it appropriate for a wide range of applications such as smart surveillance, targeted marketing, and human-computer interaction. In conclusion, our research provides a comprehensive solution for real-time age and gender recognition using CNNs, bridging the gap between cutting-edgeaccuracy and practical usability. This work advances the field of computer vision by providing robust and efficient demographic estimation from facial photos in real-time circumstances.

How To Cite (APA)

B. Balakishan, K. Srinitha, T. Shivani, B. Vijay, & T. Vikas (May-2024). AGE AND GENDER CLASSIFICATION USING DEEP LEARNING WITH IMAGES . INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(5), h451-h455. https://ijnrd.org/papers/IJNRD2405764.pdf

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Other Publication Details

Paper Reg. ID: IJNRD_222727

Published Paper Id: IJNRD2405764

Research Area: Engineering

Author Type: Indian Author

Country: -, -, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2405764.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2405764

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