Age And Gender Recognition Based On Caffe Deep Learning Module

Registration ID: IJNRD_216837

Published ID: IJNRD2404247

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M.D.Charan, A.Dineshkumar, Mrs.P.Divya

Data Science, Artificial Intelligence, Machine Learning, Hyper Text Markup Language, Convolutional Neural Network, Deep Learning, Deep Neural Network, Prototxt-Prototype Text, Computer vision, Numerical Python, Lightning Memory-Mapped Database, Application Programming Interface, -Hierarchical Data Format, Caffe Module, Classification, Regression, Data Preprocessing, Accuracy.

The ‘Gender and Age Detection’ is a machine learning project based on computer visioning. Through this Data Science Project, it is based on the practical application of CNN i.e., the convolutional neural networks, this use models that are trained by ‘Tal Hassner’ and ‘Gil Levi’ for ‘Adience’ dataset. Along with this, it uses some files such as –. pb, prototxt, .pbtxt, & .Caffe model files. It’s a very practical project as you will create a model that can detect any human being’s age & gender through analyses of single face detection via an image. So, with this gender classification in a man or a woman can be classified. Also, the age can be classified among the ranges of 0-2/ 4-6/ 8- 2/ 15-20/ 25-32/ 38-43/ 48-53/ 60-100.we implement classification model for gender recognition and regression model for age recognition, which will predict the better accuracy needed for this project. Age and gender recognition technologies leverage various methods, including image processing and machine learning algorithms, to analyze facial features and determine a person's age and gender. While HTML (Hypertext Markup Language) itself is primarily used for structuring the content of web pages, the implementation of age and gender recognition typically involves a combination of HTML with other technologies, such as JavaScript and server-side programming languages. Here's an abstract outlining the potential uses of HTML in the context of age and gender recognition: In conclusion, HTML serves as the cornerstone for developing intuitive and user-friendly interfaces in age and gender recognition applications. Its role in structuring content, handling user interactions, and facilitating communication with backend services underscores its significance in creating a cohesive and engaging experience for users interacting with these innovative technologies. Furthermore, HTML supports the integration of APIs (Application Programming Interfaces) that connect web applications with external services, allowing seamless communication between the frontend and backend components.

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M.D.Charan, A.Dineshkumar, & Mrs.P.Divya (April-2024). Age And Gender Recognition Based On Caffe Deep Learning Module. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), c162-c167. https://ijnrd.org/papers/IJNRD2404247.pdf

Volume 9 Issue 4, April-2024

Pages : c162-c167

Paper Reg. ID: IJNRD_216837

Published Paper Id: IJNRD2404247

Research Area: Engineering

Author Type: Indian Author

Country: Villupuram , Tamil Nadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404247.pdf

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