Effectiveness of Using Artificial Intelligence for Early Child Development Screening
This study presents a novel approach to recognizing emotions in infants using machine learning models. To address the lack of infant-specific datasets, a custom dataset of infants' faces was created by extracting images from the AffectNet dataset. The dataset was then used to train various mach...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Tecno Scientifica
2023
|
| Subjects: | |
| Online Access: | http://eprints.sunway.edu.my/2343/ http://eprints.sunway.edu.my/2343/1/134.pdf |
| _version_ | 1848802264555192320 |
|---|---|
| author | Gau, Michael-Lian Ting, Huong-Yong Toh, Teck-Hock Wong, Pui-Ying Woo, Pei Jun * Wo, Su-Woan Tan, Gek-Ling |
| author_facet | Gau, Michael-Lian Ting, Huong-Yong Toh, Teck-Hock Wong, Pui-Ying Woo, Pei Jun * Wo, Su-Woan Tan, Gek-Ling |
| author_sort | Gau, Michael-Lian |
| building | SU Institutional Repository |
| collection | Online Access |
| description | This study presents a novel approach to recognizing emotions in infants using machine learning models. To address the lack of infant-specific datasets, a custom dataset of infants' faces was created by extracting images from the AffectNet dataset. The dataset was then used to train various machine learning models with different parameters. The best-performing model was evaluated on the City Infant Faces dataset. The proposed deep learning model achieved an accuracy of 94.63% in recognizing positive, negative, and neutral facial expressions. These results provide a benchmark for the performance of machine learning models in infant emotion recognition and suggest potential applications in developing emotion-sensitive technologies for infants. This study fills a gap in the literature on emotion recognition, which has largely focused on adults or children and highlights the importance of developing infant-specific datasets and evaluating different parameters to achieve accurate results. |
| first_indexed | 2025-11-14T21:20:35Z |
| format | Article |
| id | sunway-2343 |
| institution | Sunway University |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T21:20:35Z |
| publishDate | 2023 |
| publisher | Tecno Scientifica |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | sunway-23432023-08-30T03:11:39Z http://eprints.sunway.edu.my/2343/ Effectiveness of Using Artificial Intelligence for Early Child Development Screening Gau, Michael-Lian Ting, Huong-Yong Toh, Teck-Hock Wong, Pui-Ying Woo, Pei Jun * Wo, Su-Woan Tan, Gek-Ling BF Psychology Q Science (General) This study presents a novel approach to recognizing emotions in infants using machine learning models. To address the lack of infant-specific datasets, a custom dataset of infants' faces was created by extracting images from the AffectNet dataset. The dataset was then used to train various machine learning models with different parameters. The best-performing model was evaluated on the City Infant Faces dataset. The proposed deep learning model achieved an accuracy of 94.63% in recognizing positive, negative, and neutral facial expressions. These results provide a benchmark for the performance of machine learning models in infant emotion recognition and suggest potential applications in developing emotion-sensitive technologies for infants. This study fills a gap in the literature on emotion recognition, which has largely focused on adults or children and highlights the importance of developing infant-specific datasets and evaluating different parameters to achieve accurate results. Tecno Scientifica 2023 Article PeerReviewed text en cc_by_nc_4 http://eprints.sunway.edu.my/2343/1/134.pdf Gau, Michael-Lian and Ting, Huong-Yong and Toh, Teck-Hock and Wong, Pui-Ying and Woo, Pei Jun * and Wo, Su-Woan and Tan, Gek-Ling (2023) Effectiveness of Using Artificial Intelligence for Early Child Development Screening. Green Intelligent Systems and Applications, 3 (1). pp. 1-13. ISSN 2809-1116 https://doi.org/10.53623/gisa.v3i1.229 10.53623/gisa.v3i1.229 |
| spellingShingle | BF Psychology Q Science (General) Gau, Michael-Lian Ting, Huong-Yong Toh, Teck-Hock Wong, Pui-Ying Woo, Pei Jun * Wo, Su-Woan Tan, Gek-Ling Effectiveness of Using Artificial Intelligence for Early Child Development Screening |
| title | Effectiveness of Using Artificial Intelligence for Early Child Development Screening |
| title_full | Effectiveness of Using Artificial Intelligence for Early Child Development Screening |
| title_fullStr | Effectiveness of Using Artificial Intelligence for Early Child Development Screening |
| title_full_unstemmed | Effectiveness of Using Artificial Intelligence for Early Child Development Screening |
| title_short | Effectiveness of Using Artificial Intelligence for Early Child Development Screening |
| title_sort | effectiveness of using artificial intelligence for early child development screening |
| topic | BF Psychology Q Science (General) |
| url | http://eprints.sunway.edu.my/2343/ http://eprints.sunway.edu.my/2343/ http://eprints.sunway.edu.my/2343/ http://eprints.sunway.edu.my/2343/1/134.pdf |