Predictors Based on Convolutional Neural Networks for the Movement Strategy of Trainable Agents for Building Customized Image Descriptors

We present a description of various custom image descriptor modifications that are used as part of an image classification pipeline with text elements. The problem under consideration is related to the classification of images of commercial facades by the type of services provided. Some of the proposed descriptor types are presented for the first time and demonstrate state-of-the-art performance on open datasets. In our study, we used a special type of descriptor for image areas with text based on traces of the movement of agents. The traces in question are generated using parameterized movement strategies, which are presented and compared in this article.