Down syndrome detection using modified adaboost algorithm
- Title
- Down syndrome detection using modified adaboost algorithm
- Creator
- Vincy Devi V.K.; Rajesh R.
- Description
- In human body genetic codes are stored in the genes. All of our inherited traits are associated with these genes and are grouped as structures generally called chromosomes. In typical cases, each cell consists of 23 pairs of chromosomes, out of which each parent contributes half. But if a person has a partial or full copy of chromosome 21, the situation is called Down syndrome. It results in intellectual disability, reading impairment, developmental delay, and other medical abnormalities. There is no specific treatment for Down syndrome. Thus, early detection and screening of this disability are the best styles for down syndrome prevention. In this work, recognition of Down syndrome utilizes a set of facial expression images. Solid geometric descriptor is employed for extracting the facial features from the image set. An AdaBoost method is practiced to gather the required data sets and for the categorization. The extracted information is then assigned and used to instruct the Neural Network using Backpropagation algorithm. This work recorded that the presented model meets the requirement with 98.67% accuracy. 2021 Institute of Advanced Engineering and Science. All rights reserved.
- Source
- International Journal of Electrical and Computer Engineering, Vol-11, No. 5, pp. 4281-4288.
- Date
- 2021-01-01
- Publisher
- Institute of Advanced Engineering and Science
- Subject
- AdaBoost algorithm; Backpropagation; Bayes classifier; Down syndrome; Facial points
- Coverage
- Vincy Devi V.K., Department of Computer Science, Bharathiar University, Coimbatore, India; Rajesh R., Department of Computer Science, CHRIST (Deemed to Be University), Bangalore, India
- Rights
- All Open Access; Gold Open Access; Green Open Access
- Relation
- ISSN: 20888708
- Format
- Online
- Language
- English
- Type
- Article
Collection
Citation
Vincy Devi V.K.; Rajesh R., “Down syndrome detection using modified adaboost algorithm,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/15637.