Age & Gender Recognition System By Using Machine Learning
Predictions of age and gender on the basis of pre-defined unfiltered real faces. Using the concepts of deep learning and the Adience dataset (trained with CNN-Convolutional Neural Networks) we created a python based application to detect faces and classify them according to age and gender. &n
2025-06-28 16:30:09 - Adil Khan
Age & Gender Recognition System By Using Machine Learning
Project Area of Specialization Computer ScienceProject SummaryPredictions of age and gender on the basis of pre-defined unfiltered real faces. Using the concepts of deep learning and the Adience dataset (trained with CNN-Convolutional Neural Networks) we created a python based application to detect faces and classify them according to age and gender.
SCOPE:
- Similar to the task of face recognition / Retina scan / Speech recognition for commercial use (organizations and institutions mainly).
- Significant role in Multimedia Retrieval and Human Machine Interaction.
- Replacing the current detection systems with this phenomena to increase the efficiency and accuracy even further.
- Using better versions (image processing) for the security purposes; can be upgraded.
- This system can lead to many potential uses like in the field of HCI, surveillance system, effective marketing or in customizing apps etc.
ACHIEVEMENTS:
- Based on facial attributes creating a batter and safer system to classify real human images.
- Usage of latest technological feature for classification of age and gender, providing the accurate and efficient output.
- Smart features used for the fully automatic system using image processing.
Project Objectives
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The main objective of this project work is to build a gender and age detector that can guess the gender and age of the person in a picture using Deep Learning and Adience dataset.
- The system should be able to detect and classify faces in images and gender classes.
- The system should evaluate and configure available models for face detection and age/gender classification.
In this Python Project, we will use Deep Learning to accurately identify the gender and age of a person from a single image of a face. We will use the models that predicted gender may be one of ‘Male’ and ‘Female’, and the predicted age may be one of the following ranges- (0 – 2), (4 – 6), (8 – 12), (15 – 20), (25 – 32), (38 – 43), (48 – 53), (60 – 100) (8 nodes in the final softmax layer). It is very difficult to accurately guess an exact age from a single image because of factors like makeup, lighting, obstructions, and facial expressions. And so, we make this a classification problem instead of making it one of regression.
The objectives of the project are mainly to detect faces, classify into male/female, classify into one of the 8 age ranges then put the results in image and then display it. we’ll use the Adience dataset, The images dataset has been collected from many albums which will be used to compare the user image. The dataset almost contains 27,000 photos in around 1 GB file size.
Benefits of the ProjectThe advantages and gains that are delivered by this project are as follows:
- By using this software one cannot lie about their age because this software has an ability to detect real age.
- This software is beneficiary in rural areas where lack of hospitals and people doesn’t have their birth certificate and they don’t know about their age especially in developing countries.
- This software is also beneficiary for games, by using face recognition system to detect player’s gender for assigning gaming character.
- This can also be used as entertainment purpose in social media apps.
- This recognition model is also beneficiary for intelligent security to track moving objects, detect abnormal behaviors, and facilitate the security investigation off criminals who intentionally try to hide their identity information.
The Technical details of this age and gender detection software can be elaborate as:
- In this software system raspberry pi model and camera module are connected together with an internet cable.
- The raspberry pi and raspberry camera module are then connected with the desktop for viewing the output on screen.
- The working of camera can be expound as, the camera captures the image of a person for detecting purpose.
- The captured image transfer to the software for further processing.
- The system extracts the features of a person from image then start working on reorganization of age and gender of a person.
- When final result was generated, then sent it to display an output.
| The main objective of this project work is to build a gender and age detector that can guess the gender and age of the person in a picture using Deep Learning and Adience dataset.
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