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Facial expression recognition (FER) has a significant impact on evaluating candidates in recruitment interviews, as it provides valuable information about their emotional states and non-verbal cues. In this paper, a new approach was proposed that relies on ResNeXt-101 to evaluate candidates in recruitment interviews. We perform an experimental evaluation of two facial expression databases, CK+ and FER + . Our suggested approach, which shows a considerable enhancement in the recognition rate compared to other used methods, gets 99.49 and 85.08% in terms of accuracy on CK+ and FER+ respectively.

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Enhancing Candidate Evaluation in Recruitment Interviews Based ResNext-101 for Facial Expression Recognition

  • 会议论文

  • 发表日期：

    2025年

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  • Kaoutar Khayyiba,
  • Aouatif Amine,
  • Bouchra Nassih

摘要

Facial expression recognition (FER) has a significant impact on evaluating candidates in recruitment interviews, as it provides valuable information about their emotional states and non-verbal cues. In this paper, a new approach was proposed that relies on ResNeXt-101 to evaluate candidates in recruitment interviews. We perform an experimental evaluation of two facial expression databases, CK+ and FER + . Our suggested approach, which shows a considerable enhancement in the recognition rate compared to other used methods, gets 99.49 and 85.08% in terms of accuracy on CK+ and FER+ respectively.