Method For Applying Learning Data Augmentaion To Deep Learning Model, Apparatus And Method For Classifying Images Using Deep Learning

摘要

The present invention proposes a learning data expansion method that expands limited learning data using a Gabor filter even if training data for deep learning-based image processing is insufficient, and can be applied to an image classification process executed in the machine vision of the manufacturing industry. It relates to an image classification apparatus and a method thereof. According to the present invention, the learning data can be easily and simply expanded to secure sufficient learning data by using a filter characteristic change method for changing the filter parameter of the Gabor filter. In addition, the present invention can improve the success rate of image classification by improving the reliability of the deep learning model by learning a deep learning model based on training data sufficiently secured by a filter characteristic change method of a Gabor filter.