Abstract:
Results of neural networks (NN) application to the problem
of detecting neoplasms on computer tomograms of the lungs with limited amount
of data are presented. Much attention is paid to the analysis and preprocessing
of images as a factor improving the NN quality. The problem of NN overfitting
and ways to solve it are considered. Results of the presented experiments allow
drawing a conclusion about the efficiency of applying individual NN architectures
in combination with data preprocessing methods to detection problems even
in cases of a limited training set and a small size of detected objects.
Key words and phrases:object detection, image processing, neural networks, YOLO.