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The Maximal Likelihood Enumeration Method for the Problem of Classifying Piecewise Regular Objects
Automation and Remote Control. 2016. Vol. 77. No. 3. P. 443-450.
We study the recognition problem for composite objects based on a probabilistic model of a piecewise regular object with thousands of alternative classes. Using the model’s asymptotic properties, we develop a new maximal likelihood enumeration method which is optimal (in the sense of choosing the most likely reference for testing on every step) in the class of “greedy” algorithms of approximate nearest neighbor search. We show experimental results for the face recognition problem on the FERET dataset. We demonstrate that the proposed approach lets us reduce decision making time by several times not only compared to exhaustive search but also compared to known approximate nearest neighbors techniques.
Savchenko A., Lecture Notes in Computer Science 2015 Vol. 9124 P. 236-245
The insufficient performance of statistical recognition of composite objects (images, speech signals) is explored in case of medium-sized database (thousands of classes). In contrast to heuristic approximate nearest-neighbor methods we propose a statistically optimal greedy algorithm. The decision is made based on the Kullback-Leibler minimum information discrimination principle. The model object to be checked at ...
Added: July 5, 2015
Savchenko A., Optical Memory and Neural Networks (Information Optics) 2017 Vol. 26 No. 2 P. 129-136
We analyzed the way to increase computational efficiency of video-based image recognition methods with matching of high dimensional feature vectors extracted by deep convolutional neural networks. We proposed an algorithm for approximate nearest neighbor search. At the first step, for a given video frame the algorithm verifies a reference image obtained when recognizing the previous ...
Added: June 30, 2017
Статистическое распознавание образов на основе вероятностной нейронной сети с проверкой однородности
Savchenko A., Искусственный интеллект и принятие решений 2013 № 4 С. 45-56
Statistical pattern recognition was reduced to the hypothesis test for homogeneity. The probabilistic neural network (PNN) modification was proposed to achieve its optimal decision in terms of minimum Bayes-risk. The comparative analysis' results of the proposed modification with an original PNN were presented in a problem of automatic author identification ...
Added: December 23, 2013
Savchenko A., Автоматика и телемеханика 2016 № 3 С. 99-108
Исследуется задача распознавания составных объектов на основе вероятностной модели кусочно-однородного объекта при наличии тысяч альтернативных классов. Используя асимптотические свойства модели, разработан новый метод максимально правдоподобного перебора, который является оптимальными (в смысле выбора для проверки на каждом этапе максимально правдоподобного эталона) среди класса “жадных” алгоритмов приближенного поиска ближайшего соседа. Приведены результаты эксперимента в задаче распознавания лиц ...
Added: March 25, 2016
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., Belova N. S., Savchenko Lyudmila V., Optical Memory and Neural Networks (Information Optics) 2018 Vol. 27 No. 1 P. 23-31
We discuss the video classification problem with the matching of feature vectors extracted using deep convolutional neural networks from each frame. We propose the novel recognition method based on representation of each frame as a sequence of fuzzy sets of reference classes whose degrees of membership are defined based on asymptotic distribution of the Kullback–Leibler ...
Added: February 9, 2018
Savchenko A., Belova N. S., Expert Systems with Applications 2018 Vol. 108 P. 170-182
The paper deals with unconstrained face recognition task for the small sample size problem based on computation of distances between high-dimensional off-the-shelf features extracted by deep convolution neural network. We present the novel statistical recognition method, which maximizes the likelihood (joint probabilistic density) of the distances to all reference images from the gallery set. This ...
Added: May 17, 2018
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., 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
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., Knowledge-Based Systems 2016 Vol. 91 P. 252-262
The paper is focused on an application of sequential three-way decisions and granular computing to the problem of multi-class statistical recognition of the objects, which can be represented as a sequence of independent homogeneous (regular) segments. As the segmentation algorithms usually make it possible to choose the degree of homogeneity of the features in a ...
Added: December 4, 2015
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
Savchenko A., Belova N. S., / Cornell University. Series "Working papers by Cornell University". 2017.
The paper deals with the still-to-video face recognition for the small sample size problem based on computation of distances between high-dimensional deep bottleneck features. We present the novel statistical recognition method, in which the still-to-video recognition task is casted into Maximum A Posteriori estimation. In this method we maximize the joint probabilistic density of the ...
Added: August 29, 2017
Savchenko A., Компьютерная оптика 2017 Т. 41 № 3 С. 422-430
In this paper we focus on the image recognition problem in the case of small sample size based on the nearest neighbor rule and matching of high-dimensional feature vectors extracted with the deep convolutional neural network. We propose the novel recognition algorithm based on the maximum likelihood method for the joint density of dissimilarities between ...
Added: July 8, 2017
Savchenko A., Заводская лаборатория. Диагностика материалов 2014 Т. 80 № 3 С. 70-80
Рассмотрена задача статистического распознавания объектов со сложной структурой. Предложена математическая модель образа как последовательности выборок независимых одинаково распределенных векторов признаков. На основе этой модели и классического байесовского подхода задача распознавание сведена к проверке гипотез об однородности выборок. Представлены результаты экспериментального исследования в задачах классификации лиц и распознавании изолированных слов русской речи. ...
Added: April 8, 2014
Savchenko A., Машинное обучение и анализ данных 2015 Т. 1 № 11 С. 1500-1516
Исследуется проблема малых выборок в задаче статистического распознавания образов на основе методов ближайших соседей, точность которых во многом определяется выбранной мерой близости, при этом их реализация в режиме реального времени может оказаться невозможной уже при наличии тысяч классов. Для преодоления указанных проблем предложен новый подход к разработке классификаторов с посегментным анализом однородности и быстрой последовательной ...
Added: September 10, 2015
Savchenko A., Switzerland : Springer, 2016
A unified methodology for categorizing various complex objects is presented in this book. Through probability theory, novel asymptotically minimax criteria suitable for practical applications in imaging and data analysis are examined including the special cases such as the Jensen-Shannon divergence and the probabilistic neural network. An optimal approximate nearest neighbor search algorithm, which allows faster ...
Added: April 12, 2016
М. : Издательский центр «Российский государственный гуманитарный университет», 2019
Сборник включает 27 докладов международной конференции по компьютерной лингвистике и интеллектуальным технологиям «Диалог 2019», не вошедшие в ежегодник «Компьютерная лингвистика и интеллектуальные технологии», но рекомендованные Программным Комитетом к представлению на конференции. Для специалистов в области теоретической и прикладной лингвистики и интеллектуальных технологий. ...
Added: December 10, 2019
Karpov V. E., Karpova I. P., Procedia Engineering 2015 Vol. 100 P. 1459-1468
Work solutions are proposed for problems of leader definition and role distribution in homogeneous groups of robots. It is shown that transition from a swarm to a collective of robots with hierarchical organization is possible using exclusively local interaction. The local revoting algorithm is central to the procedure for choice of leader while redistribution of roles can ...
Added: March 14, 2015
Chernyshev S. V., Cherepanov E. A., Pankratiev E. V. et al., Journal of Mathematical Sciences 2005 Vol. 128 No. 6 P. 3487-3495
Added: January 27, 2014
Chuprikov P., Nikolenko S. I., Davydow A. et al., IEEE Transactions on Networking 2018 Vol. 26 No. 1 P. 342-355
Modern network elements are increasingly required to deal with heterogeneous traffic. Recent works consider processing policies for buffers that hold packets with different processing requirements (number of processing cycles needed before a packet can be transmitted out) but uniform value, aiming to maximize the throughput, i.e., the number of transmitted packets. Other developments deal with ...
Added: March 14, 2018
Goncharov R., Сапанов П. М., Яшунский А. Д., Социология власти 2013 № 3 С. 57-72
В статье представлена технология, позволяющая собирать в полевых исследованиях пространственно локализованные данные об объектах городской среды. Технология основана на автоматической привязке фотографий к пространственным координатам. Приведен план полевых и камеральных мероприятий, предложены варианты ГИС-обработки собираемых таким образом данных. В качестве примера приведены данные об использовании белорусского языка в общественном пространстве городов Белоруссии. ...
Added: April 12, 2015
Sotnikova S., Динамика сложных систем 2012 № 3 С. 84-87
In article is described designed programme complex of the physical processes modeling, which also allows to conduct the identification printed node parameters (the physical model). On printed node designed the on-board secondary power supply source is realized. For it are designed relationship interfaces of controlling program with the known program of modeling and optimization. ...
Added: December 5, 2014
Skoptsov K. A., Sheshenin S., Galatenko V. V. et al., International Journal of Applied Mechanics 2016 Vol. 8 No. 2 P. 1650016-01-1650016-18
We present a method for evaluating elastic properties of a composite material produced by molding a resin filled with short elastic fibers. A flow of the filled resin is simulated numerically using a mesh-free method. After that, assuming that spatial distribution and orientation of fibers are not significantly changed during polymerization, effective elastic moduli of ...
Added: May 22, 2016