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Full-Text Articles in Computer Engineering
Analysis Of Gait Characteristics In Mentally Handicapped Individuals, Prakriti Parijat, Jian Liu, Thurmon E. Lockhart, Courtney Haynes
Analysis Of Gait Characteristics In Mentally Handicapped Individuals, Prakriti Parijat, Jian Liu, Thurmon E. Lockhart, Courtney Haynes
Computer Sciences and Electrical Engineering Faculty Research
Physical and motor dysfunctions in mentally handicapped individuals predispose them to a higher risk of slip and fall accidents. It is estimated that over 60 million people are currently suffering with some level of developmentally related cognitive impairment (American Disability Act ADA, 2000). Mental retardation occurs in 2.5-3% of the general population. About 6-7.5 million mentally retarded individuals live in the United States alone (ADA, 2000). Slip induced fall accidents are a primary source of injury in people with mental retardation (MR). Often, the incidence of falls among this population is compounded by other disabilities such as autism, seizure, and …
Least Squares Support Vector Machine Based Classification Of Abnormalities In Brain Mr Images, S. Thamarai Selvi, D. Selvathi, R. Ramkumar, Henry Selvaraj
Least Squares Support Vector Machine Based Classification Of Abnormalities In Brain Mr Images, S. Thamarai Selvi, D. Selvathi, R. Ramkumar, Henry Selvaraj
Electrical & Computer Engineering Faculty Research
The manual interpretation of MRI slices based on visual examination by radiologist/physician may lead to missing diagnosis when a large number of MRIs are analyzed. To avoid the human error, an automated intelligent classification system is proposed. This research paper proposes an intelligent classification technique to the problem of classifying four types of brain abnormalities viz. Metastases, Meningiomas, Gliomas, and Astrocytomas. The abnormalities are classified based on Two/Three/ Four class classification using statistical and textural features. In this work, classification techniques based on Least Squares Support Vector Machine (LS-SVM) using textural features computed from the MR images of patient are …