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Image Recognition Using Kullback-Leibler Information Discrimination
P. 102–112.
The problem of automatic image recognition based on the minimum information discrimination principle is formulated and solved. Color histograms comparison in the Kullback–Leibler information metric is proposed. It’s combined with method of directed enumeration alternatives as opposed to complete enumeration of competing hypotheses. Results of an experimental study of the Kullback-Leibler discrimination in the problem of face recognition with a large database are presented. It is shown that the proposed algorithm is characterized by increased accuracy and reliability of image recognition.
In book
Vol. 758. , M.: Higher School of Economics Publishing House, 2011.
Aleksei Samarin, Aleksei Toropov, Dzestelova A. et al., , in: Proceedings of the 35th Conference of Open Innovations Association FRUCT, Tampere, Finland, 24-26 April 2024Vol. 35.: FRUCT Oy, 2024. P. 659–664.
This research endeavor is dedicated to the integration of specialized attentional mechanisms within the intricate web of deep neural network architectures aimed at discerning indications of lung carcinoma from monochromatic snapshots derived from computerized axial tomography. Within this exploration, we propose a myriad of adaptations to the traditional non-local blocks, infusing them with bespoke attentional ...
Added: September 19, 2026
Shchuka I., Miftakhov S., Patrushev V. et al., , in: 2020 International Conference Engineering and Telecommunication (En&T).: IEEE, 2020. P. 1–5.
The paper presents a method for meal recognition, ingredient extraction and recipe suggestion in the Russian language. The proposed algorithm consists of several consecutive stages. On the first stage the model extracts a list of ingredients from a photo of the dish, based on which recipes on the second stage are selected. Two ingredient extraction ...
Added: June 14, 2026
Tsybina Y., Kastalskiy I., Krivonosov M. et al., Neural Computing and Applications 2023 Vol. 34 No. 11 P. 9147 –9160
Modeling the neuronal processes underlying short-term working memory remains the focus of many theoretical studies in neuroscience. In this paper, we propose a mathematical model of a spiking neural network (SNN) which simulates the way a fragment of information is maintained as a robust activity pattern for several seconds and the way it completely disappears ...
Added: April 9, 2025
Головин Р. Д., Zunin V., В кн.: Межвузовская научно-техническая конференция студентов, аспирантов и молодых специалистов имени Е.В. Арменского. Материалы конференции.: М.: МИЭМ НИУ ВШЭ, 2021. С. 120–122.
В работе проводится обзор различных способов реализации нейронной сети для распознавания изображения на примере набора данных MNIST. Дается анализ используемых библиотек и методов их применения в области распознавания объектов. ...
Added: September 25, 2022
Savchenko A., Belova N. S., Expert Systems with Applications 2022 Vol. 207 Article 117885
In this paper, the computational complexity of the probabilistic neural network for the classification of high-dimensional data is improved. At first, the class probability densities are estimated by using only a few principal components of an observed point. The Gaussian–Parzen kernel is replaced by the orthogonal series estimates of class-conditional densities for each principal component using the Fourier series to speed ...
Added: June 29, 2022
Anna Beketova, Makarov I., , in: Advances in Computational Intelligence: 16th International Work-Conference on Artificial Neural Networks, IWANN 2021, Virtual Event, June 16–18, 2021, Proceedings, Part II.: Cham: Springer, 2021. Ch. 3 P. 28–42.
*Реализация соц. сети Instagram запрещена на территории России по основаниям осуществления экстремистской деятельности.
Instagram is one of the most popular photos sharing services. For more convenient content search people use hashtags (#nature, #love, etc.) in posts with photos. The author’s aim is to make hashtag prediction possible and convenient for users.
The paper provides a reader with ...
Added: September 1, 2021
Savchenko A., Information Sciences 2021 Vol. 560 P. 370–385
A novel image recognition algorithm based on sequential three-way decisions is introduced to speed up the inference in a convolutional neural network. In contrast to the majority of existing studies, our approach does not require a special procedure to train a neural network, and thus it can be used with arbitrary architectures including pre-trained convolutional ...
Added: February 25, 2021
Savchenko A., Записки научных семинаров ПОМИ РАН 2021 Т. 499 С. 267–283
In this paper fast image recognition techniques based on statistical sequential analysis are discussed. We examine the possibility to sequentially process the principal components and organize a convolutional neural net- work with early exits. Particular attention is paid to sequentially learn multi-task lightweight neural network model to predict several facial at- tributes (age, gender and ...
Added: January 27, 2021
Savchenko A., , in: Proceedings of International Joint Conference on Neural Networks 2020 (IJCNN 2020).: Piscataway: IEEE, 2020. P. 1–8.
In this paper the problem of high computational complexity of deep convolutional nets in image recognition is considered. An existing framework of adaptive neural networks is extended by appending the separate classifier to intermediate layers. The hierarchical representations of the input image are sequentially analyzed. If the first classifier returns rather high confidence score, the ...
Added: October 15, 2020
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 L., Информационные технологии 2019 Т. 25 № 5 С. 313–318
We consider a problem of computer assisted language and pronunciation learning based on the deep learning methods and the information theory of speech perception. In order to improve the efficiency of testing of pronunciation quality, we propose to train a convolutional neural network using the best reference utterances from the user. The experimental results proved ...
Added: May 29, 2019
Savchenko A., Information Sciences 2019 Vol. 489 P. 18–36
The paper addresses the issue of insufficient speed of image recognition methods if the number of classes is rather large. We propose the novel algorithm based on sequential three-way decisions and a formal description of granular computing. Each image is associated with principal component scores of the high-dimensional features extracted by deep convolution neural network. ...
Added: March 20, 2019
Savchenko A., , in: International Joint Conference on Rough Sets, Springer, Cham.: Springer, 2017. P. 264–277.
In this paper it is proposed to improve performance of the automatic speech recognition by using sequential three-way decisions. At first, the largest piecewise quasi-stationary segments are detected in the speech signal. Every segment is classified using the maximum a-posteriori (MAP) method implemented with the Kullback-Leibler minimum information discrimination principle. The three-way decisions are taken ...
Added: October 26, 2018
Savchenko L., Телекоммуникации 2017 № 5 С. 42–48
The paper is devoted to the automatic assessment of phoneme pronunciation quality for computer assisted language learning systems. The novel pronunciation training algorithm is proposed. In this algorithm, at first, a student has to achieve a stable pronunciation of all sounds by using the phonetic database from ideal speaker. The second, novel, stage of our ...
Added: October 24, 2018
Чумаков И. Г., Komarov M. M., , in: Workshops and work-in-progress contributions at S-BPM One 2018Vol. 2074.: CEUR Workshop Proceedings, 2018. Ch. 5 P. 71–78.
A fridge plays an important role in the kitchen in comparison to other appliances because it helps to store food products at optimal conditions for a long period of time. The ordinary refrigerators perfectly allow preserving meals but they are not effective in case of food management. Providing a remote control for home appliances extends ...
Added: May 3, 2018
A. G. Rassadin, A. V. Savchenko, , in: Proceedings of the III International Conference on Information Technologies and Nanotechnologies (ITNT).: Самара: Новая техника, 2017. P. 649–654.
In this paper, we consider the problem of insufficient runtime and memory-space complexities of contemporary deep convolutional neural networks in the problem of image recognition. A survey of recent compression methods and efficient neural networks architectures is provided. The experimental study is focused on the visual emotion recognition problem. We compare the computational speed and ...
Added: September 8, 2017
Savchenko A., Belova N. S., / 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
Khanzhina N., Zamyatina E., International Journal "Information Models and Analyses" 2015 Vol. 4 No. 3 P. 243–258
This paper describes the problem of automated pollen grains image recognition using images from microscope. This problem is relevant because it allows to automate a complex process of pollen grains classification and to determine the beginning of pollen dispersion which cause an the allergic responses. The main recognition methods are Hamming network [Korotkiy, 1992] and ...
Added: March 13, 2017