Face Recognition Attendance System using Machine Learning at IEEE Project Centers in Bangalore

This final year project leverages face recognition technology to develop an efficient attendance system using machine learning algorithms, including Support Vector Machine (SVM), Multilayer Perceptron (MLP), and Convolutional Neural Network (CNN). The system employs Deep Neural Networks (DNN) for face detection and utilizes PCA and LDA feature extraction methods for SVM and MLP approaches, while CNN processes face images directly as feature vectors. Achieving approximately 98% accuracy on a self-generated database, this IEEE-based project is ideal for computer science students seeking a high-impact project in computer vision and machine learning.

🎓 Our Comprehensive Research Support Services

Upon purchasing this project online, you will receive recorded video tutorials, comprehensive documentation, complete frontend (HTML, CSS, JavaScript) and backend (Python with SVM, MLP, CNN implementations) codes, reports, PPTs, and datasets, all sent automatically to your email. For further support, contact our technical team at +91 8088605682. Please note that once payment is made, no refunds will be issued under any circumstances.

• Completed Working Code

  Receive fully functional and tested code for the face recognition attendance system, implemented using Python with SVM, MLP, and CNN algorithms.

• Comprehensive Documentation

  Get detailed documentation, including reports, PPTs, and datasets for research papers, sent automatically to your email upon purchase.

Additional Services (Charged Extra)

• One-to-One Online Developer Support

  For personalized guidance on installation and implementation, contact our technical team at +91 8088605682 to arrange one-to-one online sessions (additional charges apply).

• Customized Support

  For project customization or additional feature integration, contact our technical team at +91 8088605682 to discuss your requirements (additional charges apply).

• Offline Support

  For hands-on, in-person assistance, contact our team at +91 8088605682 to arrange offline support at our Bangalore center (additional charges apply).

This is one of the best IEEE Machine Learning project ideas for final-year students. The project includes complete frontend (HTML, CSS, JavaScript) and backend (Python with SVM, MLP, CNN implementations) codes, along with detailed explanations to ensure thorough understanding. Smart AI Technologies offers thorough guidance, complete support in implementing the face recognition system, and content for your report and IEEE paper publication, making it a commercially viable solution for applications in attendance management, security, and beyond.