CNN CNN-BASED LEARNING METHOD LEARNING DEVICE FOR SELECTING USEFUL TRAINING DATA AND TEST METHOD TEST DEVICE USING THE SAME

摘要

A convolutional neural network (CNN)-based learning method for selecting useful training data is provided. The CNN-based learning method includes the steps of a learning device: (a) instructing a first CNN module (i) to generate a first feature map, and instructing a second CNN module to generate a second feature map; and (ii) to generate a first output indicating identification information or location information of an object by using the first feature map, and calculate a first loss by referring to the first output and its corresponding GT image; (b) instructing the second CNN module (i) to change a size of the first feature map and integrate the first feature map with the second feature map, to generate a third feature map; and (ii) to generate a fourth feature map and to calculate a second loss; and (c) backpropagating an auto-screener′s loss generated by referring to the first loss and the second loss.