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Emotion recognition is a crucial component with broad applications in technology and healthcare industries specifically in human–computer interaction. To improve emotion recognition accuracy, this research introduces an innovative technique that integrates face detection with Convolutional Neural Networks (CNNs). Using the Fer2013 dataset, the approach consists of carefully identifying faces in images as a preprocessing step, followed by training a CNN network to identify emotions and create corresponding emojis. After conducting extensive testing and assessment, it is determined that after employing a face detection algorithm the suggested framework is effective in both correctly identifying emotions and producing visually appealing emojis. This helps to create an interface for emotional communication that is more user-friendly and captivating.

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Facial Emotion Recognition Augmented with CNNs and Face Detection: Toward Emotive Emoji Synthesis

  • 会议论文

  • 发表日期：

    2025年

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  • R. Suguna,
  • N. Mohana Suganthi,
  • P. S. Neethu,
  • J. Suriya Prakash

摘要

Emotion recognition is a crucial component with broad applications in technology and healthcare industries specifically in human–computer interaction. To improve emotion recognition accuracy, this research introduces an innovative technique that integrates face detection with Convolutional Neural Networks (CNNs). Using the Fer2013 dataset, the approach consists of carefully identifying faces in images as a preprocessing step, followed by training a CNN network to identify emotions and create corresponding emojis. After conducting extensive testing and assessment, it is determined that after employing a face detection algorithm the suggested framework is effective in both correctly identifying emotions and producing visually appealing emojis. This helps to create an interface for emotional communication that is more user-friendly and captivating.