TRAINING DATA SELECTION METHOD FOR ACTIVE LEARNING, TRAINING DATA SELECTION DEVICE FOR ACTIVE LEARNING AND IMAGE ANALYSIS METHOD USING ACTIVE LEARNING

摘要

The disclosed technology relates to a method for selecting learning data for active learning, an apparatus, and an image analysis method using active learning, comprising: receiving, by a computing device, a plurality of images captured by CCTV using an input device; Selecting some of the images by applying random sampling to the plurality of images, by the computing device; Classifying at least one object included in each of the selected images by the computing device inputting the selected images into an object learning model; Calculating, by the computing device, an entropy for each of the selected images based on the classification result of the object learning model; And selecting, by the computing device, a certain number of images whose entropy exceeds a reference value from among the selected images or a certain number of images in the order of the highest entropy as learning data. Therefore, it is effective to increase the reliability of prediction results even with a small number of data by first training some of the label inputted data to the object learning model.