Volume 32 #3

Contents

1. Fundamental principles of odor perception for higher fatty aids V. Ì. Ganshina and E. P. Zinkevich
2. Attractors for visual attention and visual scene analysis
3. Influence of the pre-exposure of visual objects on the discrimination of sounds in children with a delay in mental and language development
4. Neural network-based feature point descriptors for registration of optical and SAR images
5. Artificial training data generation for the task of character recognition of fields of russian passport
6. Methods of training data augmentation in the task of image classification
7. Neural network model of multisensory detector vehicle presence in the classification zone of charging points
8. Learning a metric feature space with siamese networks for disparity map computation
9. A method of object recognition based on formal properties specification applied to locating objects in aerial photographs

We investigate the current relevance of the classical structured approach to recognition (the target object is described by a formal model of its structure). We suggest a method of constructing recognition systems which combine structured recognition with machine learning. The approach is demonstrated through designing and implementing a system for locating separate building in aerial photographs. We discuss further possibilities of using formal property specification languages for fast readjustment of recognition systems.

Key words: formal models, syntactic pattern recognition, neural network classifiers, detectors for geometric primitives

DOI: 10.1134/S0235009218030125

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