APPARATUS AND METHOD FOR REFINING DATA AND IMPROVING PERFORMANCE OF BEHAVIOR RECOGNITION MODEL BY REFLECTING TIME-SERIES CHARACTERISTICS OF BEHAVIOR

摘要

Provided is an apparatus for refining data and improving the performance of a behavior recognition model by reflecting time-series characteristics of a behavior. The apparatus includes: a data pre-processing unit configured to receive training data and real-time data as input, identify a missing value of sensor data, and interpolate the sensor data; a behavior recognition unit configured to, through a behavior recognition model, generate a behavior recognition classification result for the preprocessed real-time data; a data refinement unit configured to correct the behavior recognition classification result to generate a refined dataset; a learning model update unit configured to analyze a similarity of the refined dataset and, based on a result of the analysis, perform learning to generate the behavior recognition model; and an information output unit configured to express a corrected behavior recognition result to a user.