Development of Low Resource Machine Learning Models for Child Cognitive Ability Assessments-Reference-Cited by-同舟云学术

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Development of Low Resource Machine Learning Models for Child Cognitive Ability Assessments

Published:2022-12-09 Issue: Volume: Page:
ISSN:
Container-title:2022 4th International Conference on Advancements in Computing (ICAC)
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Author:

Kahawanugoda Adithya¹,Gnanarathna Kulanika¹,Meegoda Nilan¹,Monarawila Randika¹,Samarasinghe Pradeepa²,Lindamulage Asiri Gawesha²

Affiliation:

1. Faculty of Computing Sri Lanka Institute of Information Technology,Department of Computer Science and Software Engineering,Malabe,Sri Lanka

2. Faculty of Computing Sri Lanka Institute of Information Technology,Department of Information Technology,Malabe,Sri Lanka

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10025026/10025033/10025049.pdf?arnumber=10025049

Reference19 articles.

1. Student Engagement Detection Using Emotion Analysis, Eye Tracking and Head Movement with Machine Learning;sharma,2019

2. Attention Span Prediction Using Head-Pose Estimation With Deep Neural Networks

3. FOCUS: Detecting ADHD Patients by an EEG-Based Serious Game

4. Real-time Attention Span Tracking in Online Education;rahul;2020 IEEE MIT Undergraduate Research Technology Conference,2020

5. Assessment of Attention in Preschoolers

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Deep Learning-Based E-Learning Solution for Identifying and Bridging the Knowledge Gap in Primary Education;2023 International Research Conference on Smart Computing and Systems Engineering (SCSE);2023-06-29

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