Abstract
Autism Spectrum Disorder refers to a variety of conditions represented by complications in social skills, limited interests and communication that’s majoritarily non-verbal. The early signs and symptoms of the disorder were found to be noticeable at a young age. However, the clinical tests take longer to diagnose and come at a higher cost. As a result, in recent years, several studies have been made to enable autism detection through early intervention. Rough Set theory is one such efficient mathematical tool for this application. This paper introduces the concept of fuzzy-neighborhood based soft rough sets The major advantage of introducing this concept lies in the construction of fuzzy -neighborhood of each object obtained through its -reduct. This neighborhood captures those objects having similar characteristics with respect to the significant attributes. The application of this model is highlighted through autism detection by obtaining the neighborhood of the given image. The proposed model also efficiently captures the various levels of autism with great accuracy. The validation is carried out by taking real time data.
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