Acknowledgement
본 연구는 한국연구재단 4 단계 두뇌한국 21 사업 (4 단계 BK21 사업)의 지원을 받아 작성되었음(과제번호: 5199990514663).
Proceedings of the Korea Information Processing Society Conference (한국정보처리학회:학술대회논문집)
- 2023.05a
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- Pages.748-750
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- 2023
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- 2005-0011(pISSN)
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- 2671-7298(eISSN)
DOI QR Code
Trends and Future Directions in Facial Expression Recognition Technology: A Text Mining Analysis Approach
얼굴 표정 인식 기술의 동향과 향후 방향: 텍스트 마이닝 분석을 중심으로
- Insu Jeon (Department of Medical Science, Soonchunhyang University) ;
- Byeongcheon Lee (Department of AI and Big Data, Soonchunhyang University) ;
- Subeen Leem (Department of Medical Science, Soonchunhyang University) ;
- Jihoon Moon (Department of Medical Science, Soonchunhyang University)
- Published : 2023.05.18
Abstract
Facial expression recognition technology's rapid growth and development have garnered significant attention in recent years. This technology holds immense potential for various applications, making it crucial to stay up-to-date with the latest trends and advancements. Simultaneously, it is essential to identify and address the challenges that impede the technology's progress. Motivated by these factors, this study aims to understand the latest trends, future directions, and challenges in facial expression recognition technology by utilizing text mining to analyze papers published between 2020 and 2023. Our research focuses on discerning which aspects of these papers provide valuable insights into the field's recent developments and issues. By doing so, we aim to present the information in an accessible and engaging manner for readers, enabling them to understand the current state and future potential of facial expression recognition technology. Ultimately, our study seeks to contribute to the ongoing dialogue and facilitate further advancements in this rapidly evolving field.
Keywords