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This research presents the design and development of an open-source graphical user interface (GUI) integrated with a deep Convolutional Neural Network (CNN) for real-time face recognition. Here two convolutional layers has been used with 32 and 64 filters respectively. The model was rigorously tested on a two custom dataset containing 40 faces and 16 faces respectively, with images organized into two distinct folders. Achieving an accuracy of 99.14%, the system features a user-friendly GUI built using an open-source platform, ensuring accessibility for non-experts. This work offers a robust and efficient solution, demonstrating the practical application of deep learning in face recognition.

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Enhanced Face Recognition with Deep CNN and User- Friendly GUI Implementation

  • 会议论文

  • 发表日期：

    2025年

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  • Saba Mansoori,
  • Pankaj Sahu,
  • Devendra Kumar Meda

摘要

This research presents the design and development of an open-source graphical user interface (GUI) integrated with a deep Convolutional Neural Network (CNN) for real-time face recognition. Here two convolutional layers has been used with 32 and 64 filters respectively. The model was rigorously tested on a two custom dataset containing 40 faces and 16 faces respectively, with images organized into two distinct folders. Achieving an accuracy of 99.14%, the system features a user-friendly GUI built using an open-source platform, ensuring accessibility for non-experts. This work offers a robust and efficient solution, demonstrating the practical application of deep learning in face recognition.