Automated Detection of Dyslexia Symptom Based on Handwriting Image for Primary School Children
This paper presents an automated detection system to identify the present of dyslexia symptoms in primary school children based on their handwriting images. The proposed automated detection system is developed by using pattern recognition technique. Based on their handwriting images, the pattern rec...
发表在: | Procedia Computer Science |
---|---|
主要作者: | 2-s2.0-85081159240 |
格式: | Conference paper |
语言: | English |
出版: |
Elsevier B.V.
2019
|
在线阅读: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85081159240&doi=10.1016%2fj.procs.2019.12.127&partnerID=40&md5=d2ee1dce6d929e87d8f5cef3ddd59223 |
相似书籍
-
Handwriting Image Classification for Automated Diagnosis of Learning Disabilities: A Review on Deep Learning Models and Future Directions
由: Sukiman S.A.; Husin N.A.; Hamdan H.; Murad M.A.A.
出版: (2024) -
MathLexic: An assistive multimedia mathematical learning aid for dyslexia children
由: 2-s2.0-84883096645
出版: (2013) -
Bijak Membaca - Applying Phonic Reading Technique and Multisensory Approach with interactive multimedia for dyslexia children
由: 2-s2.0-84877669564
出版: (2012) -
Arabic Handwriting Classification using Deep Transfer Learning Techniques
由: 2-s2.0-85125867421
出版: (2022) -
Characteristics of ultrafine particle sources and deposition rates in primary school classrooms
由: 2-s2.0-84900803036
出版: (2014)