• Sonia Peddinti

The project on "Gender and Age Detection with OpenCV" represents a compelling venture within the domains of Data Science and Computer Vision. It explores the application of Convolutional Neural Networks (CNNs) to accurately discern both gender and approximate age from individual facial images. Recognizing the complexities inherent in real-world scenarios, such as variations in makeup, lighting conditions, and unique facial expressions, the project underscores the importance of practical and technical insights, making it a valuable asset to any data science portfolio. Moreover, given the recent surge in interest surrounding age and gender detection, this project holds significant potential for application across diverse fields. The project on "Gender and Age Detection with OpenCV" represents a compelling venture within the domains of Data Science and Computer Vision. It explores the application of Convolutional Neural Networks (CNNs) to accurately discern both gender and approximate age from individual facial images. Recognizing the complexities inherent in real-world scenarios, such as variations in makeup, lighting conditions, and unique facial expressions, the project underscores the importance of practical and technical insights, making it a valuable asset to any data science portfolio. Moreover, given the recent surge in interest surrounding age and gender detection, this project holds significant potential for application across diverse fields.

Convolutional Neural Networks (CNNs), deep learning, OpenCV, gender detection, age prediction.

"Gender and Age Detection with OpenCV", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 2, page no.f587-f594, February-2024, Available :http://www.jetir.org/papers/JETIR2402573.pdf

"Gender and Age Detection with OpenCV", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 2, page no. ppf587-f594, February-2024, Available at : http://www.jetir.org/papers/JETIR2402573.pdf