Ambiguous facial expression detection for Autism Screening using enhanced YOLOv7-tiny model.

Autism spectrum disorder is a developmental condition that affects the social and behavioral abilities of growing children. Early detection of autism spectrum disorder can help children to improve their cognitive abilities and quality of life. The research in the area of autism spectrum disorder reports that it can be detected from cognitive tests and physical activities of children. The present research reports on the detection of autism spectrum disorder from the facial attributes of children. Children with autism spectrum disorder show ambiguous facial expressions which are different from the facial attributes of normal children. To detect autism spectrum disorder from facial images, this work presents an improvised variant of the YOLOv7-tiny model. The presented model is developed by integrating a pyramid of dilated convolutional layers in the feature extraction network of the YOLOv7-tiny model. Further, its recognition abilities are enhanced by incorporating an additional YOLO detection head. The developed model can detect faces with the presence of autism features by drawing bounding boxes and confidence scores. The entire work has been carried out on a self-annotated autism face dataset. The developed model achieved a mAP value of 79.56% which was better than the baseline YOLOv7-tiny and state-of-the-art YOLOv8 Small model.
Competing Interests: Declarations Competing interests The authors declare no competing interests. Ethical statement I “Dushantha Nalin K. Jayakody” hereby declare that for the manuscript: “Ambiguous Facial Expression Detection for Autism Screening Using Enhanced YOLOv7-tiny Model” following is fulfilled: (1) The submitted work is authors’ own original work and has not been published before or submitted elsewhere for publication. (2) The submitted work reflects the authors’ own research and analysis in a truthful manner. (3) The paper meaningfully credits the contributions of co-authors. (4) The results are appropriately presented in context of previous and present research. (5) All sources are cited appropriately and added to the references Sect. (6) The related data is disclosed in the data availability Sect. (7) No research has been conducted on human participants directly. Only images have been used from the cited sources/dataset. The images illustrated in the manuscript are authors original images. (8) All authors have been personally and actively involved in substantial work leading to the paper, and will take public responsibility for its content. The violation of the Ethical Statement rules may result in severe consequences. I agree with the above statements and declare that this submission follows the policies as outlined in the Guide for Authors and in the Ethical Statement.
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