Work place: School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, 600127, India
E-mail: lavishjain307@gmail.com
Website:
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Biography
Lavish R. Jain is currently pursuing the Bachelor of Technology degree in computer science and engineering with a specialization in AI and robotics with Vellore Institute of Technology, Chennai. His research interests include AI/ML, drones, and robotics.
By Ayesha Shaik Lavish R. Jain Balasundaram A.
DOI: https://doi.org/10.5815/ijitcs.2025.05.04, Pub. Date: 8 Oct. 2025
This research work aims to utilize deep learning techniques to identify autism traits in children based on their facial features. By combining traditional convolutional approaches with attention layers, the study seeks to enhance interpretability and accuracy in identifying autism spectrum disorder (ASD) traits. The dataset includes diverse facial images of children diagnosed with ASD and neuro-typical children, ensuring comprehensive representation. Preprocessing techniques standardize and enhance image quality, mitigating biases. Integration of attention layers within the convolutional neural net-work (CNN) architecture focuses on crucial facial features, improving feature extraction and classification accuracy. This approach enhances model interpretability through eXplainable AI (XAI) techniques. Model training involves optimization and validation processes, employing hyper parameter tuning and cross-validation for robustness. The performance of this combined model yielded close to 95% accuracy outperforming existing models in terms of complexity to accuracy ratio.
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