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## Об одном способе повышения вычислительной эффективности вероятностной нейронной сети в задаче распознавания образов на основе проекционных оценок

Информационные системы и технологии. 2015. № 4(90). С. 28-38.

Savchenko A., Компьютерная оптика 2018 Т. 42 № 1 С. 149-158

In this paper we study the image recognition tasks, in which images are described by high dimensional feature vectors extracted with deep convolutional neural networks and principal component analysis. In particular, we focus on the problem of high computational complexity of statistical approach with non-parametric estimates of probability density implemented by the probabilistic neural network. ...

Added: April 11, 2018

Savchenko A., IEEE Transactions on Neural Networks and Learning Systems 2020 Vol. 31 No. 2 P. 651-660

If the training data set in image recognition task is not very large, the feature extraction with a convolutional neural network is usually applied. Here, we focus on the nonparametric classification of extracted feature vectors using the probabilistic neural network (PNN). The latter is characterized by the high runtime and memory space complexity. We propose ...

Added: November 1, 2019

Savchenko A., Lecture Notes in Computer Science 2016 Vol. 9719 P. 505-512

Probabilistic neural network (PNN) is the well-known instance-based learning algorithm, which is widely used in various pattern classification and regression tasks, if rather small number of instances for each class is available. The known disadvantage of this network is its insufficient classification computational complexity. The common way to overcome this drawback is the reduction techniques ...

Added: July 6, 2016

Savchenko A., Milov V., Optical Memory and Neural Networks (Information Optics) 2016 Vol. 25 No. 2 P. 79-87

Decision support in equipment condition monitoring systems with image processing is analyzed. Long-run accumulation of information about earlier made decisions is used to realize the adaptiveness of the proposed approach. It is shown that unlike conventional classification problems, the recognition of abnormalities uses training samples supplemented with reward estimates of earlier decisions and can be ...

Added: July 10, 2016

Savchenko A., Pattern Recognition 2017 Vol. 61 P. 459-469

An exhaustive search of all classes in pattern recognition methods cannot be implemented in real-time, if the database contains a large number of classes. In this paper we introduce a novel probabilistic approximate nearest-neighbor (NN) method. Despite the most of known fast approximate NN algorithms, our method is not heuristic. The joint probabilistic densities (likelihoods) ...

Added: August 30, 2016

Savchenko A., Optical Memory and Neural Networks (Information Optics) 2013 Vol. 22 No. 3 P. 184-192

The research subject is the computational complexity of the probabilistic neural network (PNN) in the pattern recognition problem for large model databases. We examined the following methods of increasing the efficiency of a neuralnetwork classifier: a parallel multithread realization, reducing the PNN to a criterion with testing of homogeneity of feature histograms of input and ...

Added: September 10, 2013

Dubnov Y. A., Bulychev A., Информационные технологии и вычислительные системы 2017 № 1 С. 101-111

We consider a problem of parameters estimation for gaussian mixture models widely used in data analysis and unsupervised machine learning. A new model identification method based on Bayesian aproach and the principle of maximum posterior distribution is proposed. In the article we describe the method of multiextremum density function maximum definition using sampling by Metropolis-Hastings ...

Added: December 27, 2017

Popkov Y., Popkov A., Dubnov Y. A., Математическое моделирование 2020 Т. 32 № 9 С. 35-52

We develop a new method of dimensionality reduction based on direct and inverse projection of data matrix and calculation of projectors minimizing cross-entropy functional. Concept of information capacity of matrix which is used as a restriction in a problem of optimal reduction is introduced. We conduct a comparison of proposed method with known ones based ...

Added: October 31, 2020

Karasev A. A., Starykh V., Вестник МГТУ МИРЭА 2014 Т. 4 № 5 С. 113-121

This article is devoted to a solution of the problem of collecting and classification of the expert knowledge acquired during the operation of information systems aimed to organize expert knowledge bases. As perspective approach ontological theory use is offered; it provides a basis for building mathematical model of knowledge representation. Organization of objects hierarchy is ...

Added: February 10, 2015

Savchenko A., Savchenko L. V., Lecture Notes in Artificial Intelligence 2014 Vol. 8536 P. 309-318

The problem of recognition of a sequence of objects (e.g., video-based image recognition, phoneme recognition) is explored. The generalization of the fuzzy phonetic decoding method is proposed by assuming the distribution of the classified object to be of exponential type. Its preliminary phase includes association of each model object with the fuzzy set of model ...

Added: July 25, 2014

Savchenko A., Belova N. S., International Journal of Applied Mathematics and Computer Science 2015 Vol. 25 No. 4 P. 915-925

The paper is focused on the problem of multi-class classification of composite (piecewise-regular) objects (e.g., speech signals, complex images, etc.). We propose a mathematical model of composite object representation as a sequence of independent segments. Each segment is represented as a random sample of independent identically distributed feature vectors. Based on this model and statistical ...

Added: September 10, 2015

Savchenko A., , in : Proceedings of the 24th International Conference on Pattern Recognition (ICPR). : IEEE, 2018. P. 3262-3267.

In this paper we deal with unconstrained face recognition with few training samples. The facial images are described with the off-the shelf high-dimensional features extracted with a deep convolutional neural network (CNN), which was preliminarily trained with an external very-large dataset. We focus on drawbacks of conventional probabilistic neural network (PNN), namely, low recognition performance ...

Added: December 2, 2018

Курск : Юго-Западный университет, 2017

Сборник содержит материалы XIII Международной конференции «Оптико-электронные приборы и устройства в системах распознавания образов, обработки изображений и символьной информации» (Курск, 16-19 мая 2017 г.), целью которой является ознакомление с имеющимися достижениями по созданию оптико-электронных приборов, систем и внедрению информационных технологий в научные исследования, учебный процесс и промышленность, а также координация по эффективному их применению в ...

Added: November 9, 2017

Savchenko A., Милов В. Р., В кн. : XVII ВСЕРОССИЙСКАЯ НАУЧНО-ТЕХНИЧЕСКАЯ КОНФЕРЕНЦИЯ "НЕЙРОИНФОРМАТИКА-2015": Сборник научных трудов. В 3-х частях. Ч. 3.: М. : НИЯУ МИФИ, 2015. С. 50-58.

Рассматривается задача автоматического распознавания изображений. Предложен иерархический подход к ее решению, в котором переход на более детальный уровень описания происходит только при недостаточной надежности классификации на предыдущем уровне. Представлены примеры практического применения в задаче распознания лиц по фотографии. ...

Added: October 8, 2015

Savchenko A., Computer Optics 2013 Vol. 37 No. 2 P. 254-262

The usage of the probabilistic neural network with homogeneity testing is proposed in image recognition problem. This decision is shown to be optimal in Bayesian terms if the task is formulated as a statistical testing for homogeneity of query and model images' feature sets. The problem of the lack of computing efficiency with many classes ...

Added: July 1, 2013

Savchenko A., Optimization Letters 2017 Vol. 11 No. 2 P. 329-341

This paper addresses the problem of insufficient performance of statistical classification with the medium-sized database (thousands of classes). Each object is represented as a sequence of independent segments. Each segment is defined as a random sample of independent features with the distribution of multivariate exponential type. To increase the speed of the optimal Kullback-Leibler minimum ...

Added: September 10, 2015

Kashnitsky Y., Ignatov D. I., Интеллектуальные системы. Теория и приложения 2015 Т. 19 № 4 С. 37-55

The paper makes a brief introduction into multiple classifier systems and describes a particular algorithm which improves classification accuracy by making a recommendation of an algorithm to an object. This recommendation is done under a hypothesis that a classifier is likely to predict the label of the object correctly if it has correctly classified its ...

Added: December 7, 2015

Emmanuel I. C., Mitrofanova E., Fairness of Machine Learning Algorithms in Demography / . 2022.

The paper is devoted to the study of the model fairness and process fairness of the Russian demographic dataset by making predictions of divorce of the 1st marriage, religiosity, 1st employment and completion of education. Our goal was to make classifiers more equitable by reducing their reliance on sensitive features while increasing or at least ...

Added: May 31, 2022

Savchenko A., Neural Networks 2013 Vol. 46 P. 227-241

The article is devoted to pattern recognition task with the database containing small number of samples per class. By mapping of local continuous feature vectors to a discrete range, this problem is reduced to statistical classification of a set of discrete finite patterns. It is demonstrated that Bayesian decision under the assumption that probability distributions ...

Added: June 16, 2013

Башмаков А. И., Белоозеров В. Н., Starykh V., Информационные системы и технологии 2013 № 6(80) С. 88-102

In article process of construction formal ontology of information resources system for an education, that pursues the aim to reflect representation about this sphere in the automated systems intended for creation, account, ordering, storage, search and use of these resources in educational institutions of various level is stated. The system of information resources is set ...

Added: January 16, 2014

Gostev I. M., Advanced Materials Research 2014 Vol. 837 P. 381-386

Methods of identification of the form of objects based on the signature analysis and invariant to affine transformations are considered. It is shown as these methods it is possible to apply to surface quality assurance. Questions of sensitivity of these methods are considered. Dependences of these methods on noise are brought. ...

Added: November 28, 2013

IEEE, 2018

Added: December 2, 2018

Dubnov Y. A., Искусственный интеллект и принятие решений 2020 № 2 С. 78-85

The paper considers the problem of feature selection in the classification problem. A method for selecting informative features based on a probabilistic approach and cross-entropy metrics is proposed. Several variants of the information criterion for selecting features for a binary classification problem are considered, as well as its generalization to the case of a multiclass ...

Added: October 31, 2020

Galatenko V. V., Livshitz E., Podol’skii V. et al., International Journal of Applied Mathematics 2012 Vol. 25 No. 6 P. 871-882

A method for the automated real-time classification of psychological functional state is proposed. The classification is based on discrete wavelet transform of electroencephalographic data. The method consists of two preliminary stages — global feature selection and individual tuning, and the main stage — real-time classification. All stages are fully automated. The software implementation of this ...

Added: October 30, 2015