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http://dx.doi.org/10.15207/JKCS.2021.12.9.021

Consultation Management Model based on Behavior Classification of Special-Needs Students  

Park, Won-Cheol (Division of Computer Engineering, Kongju National University)
Park, Koo-Rack (Division of Computer Science & Engineering, Kongju National University)
Publication Information
Journal of the Korea Convergence Society / v.12, no.9, 2021 , pp. 21-30 More about this Journal
Abstract
Unlike behaviors that are generally known, information regarding unspecific behaviors is insufficient. For an education or guidance regarding the unspecific behaviors, collection and management of data regarding the unspecific behaviors of special-needs students are needed. In this paper, a consultation management model based on behavior classification of special-needs students using machine learning is proposed. It collects data by photographing the behavior of special students in real time, analyzes the behavior pattern, composes a data set, and trains it in the suggestion system. It is possible to improve the accuracy by comparing the behavior of special students photographed later into the suggestion system and analyzing the results by comparing it with the existing data again. The test has been performed by arbitrarily applying unspecific behaviors that are not stored in the database, and the forecast model has accurately classified and grouped the input data. Also, it has been verified that it is possible to accurately distinguish and classify the behaviors through the feature data of the behaviors even if there are some errors in the input process.
Keywords
Special Student; Unspecified Behavior; Machine Learning; Image Processing; TensorFlow;
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