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Dish-ID: A neural-based method for ingredient extraction and further recipe suggestion.
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 architectures were tested for the first stage and three recipe matching methods for recipe suggestion are proposed. In addition, the algorithm was incorporated into the telegram-bot which provides friendly user experience. Source code is at https://github.com/Alenushldish_id_sirius.
Aleksei Samarin, Aleksei Toropov, Dzestelova A. et al., , in: Proceedings of the 35th Conference of Open Innovations Association FRUCT, 24-26 April 2024, Tampere, FinlandIssue 1.: 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
Daniil S. Yashchenko, Aleksandr Y. Romanov, Artur A. Ziazetdinov et al., IEEE Access 2026 Vol. 14 P. 4990–5001
This study presents a method for generating synthesizable Verilog code for digital integrated circuits directly from natural-language specifications. The approach combines large language models with parameter-efficient fine-tuning (specifically, Low-Rank Adaptation and Quantized Low-Rank Adaptation) together with a specialized corpus of specification-code pairs that covers common design patterns and varying task complexity. The pipeline includes automated ...
Added: February 11, 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
Cham: Springer, 2024.
This book constitutes revised selected papers from the thoroughly refereed proceedings of the 11th International Conference on Analysis of Images, Social Networks and Texts, AIST 2023, held in Yerevan, Armenia, during September 28-30, 2023.
The 24 full papers included in this book were carefully reviewed and selected from 93 submissions. They were organized in topical sections ...
Added: March 25, 2024
Kolmogorova A., М.: АйПиАр Медиа, 2024.
The textbook discusses the main resources and tools, the use of which will provide essential methodological support in conducting linguistic research of various levels and issues. The theoretical material is illustrated by practical cases from the author's experience. The publication uses the results of the project "Text as Big Data: Modelling Convergent Processes in Language ...
Added: March 18, 2024
IEEE, 2022.
Proc. of FRUCT 32 ...
Added: December 9, 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
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 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
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
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
Замятина Елена Борисовна, Ханжина Н. Е., В кн.: Высокопроизводительные вычисления на графических процессорах: материалы III Всерос. науч.-практ. конф. с междунар. участием с элементами науч. шк. для молодежи (ВВГП–2016).: Пермь: Пермский государственный национальный исследовательский университет, 2016. С. 70–81.
In this work, we describe the problem of automated pollen recognition using images from lighting microscope. Automated pollen recognition related to such important tasks as honey quality control, air quality control for helping to asthma and allergy patients, paleopalynology, forensic palynology. We describe the problem solution based on machine learning and CUDA. Extracted features and ...
Added: March 12, 2017
Romanov A., Amerikanov A., Lezhnev E. et al., Прикладная радиоэлектроника 2016 Т. 15 № 2 С. 123–126
The paper describes the development of a robotic platform for buildings. The versatility of the platform allows its applying in various fields of human activity, both in the remote control and autonomous regime. The main steps involved in creating a robotic platform are described; its characteristics and working results are given. ...
Added: October 7, 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., 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., Belova N. S., Milov V., , in: Analysis of Images, Social Networks and Texts. 4th International Conference, AIST 2015, Yekaterinburg, Russia, April 9–11, 2015, Revised Selected PapersVol. 542: Series: Communications in Computer and Information Science.: Switzerland: Springer, 2015. Ch. 2 P. 14–23.
In this paper we explore an application of the pyramid HOG (Histograms of Oriented Gradients) features in image recognition problem with small samples. A sequential analysis is used to improve the performance of hierarchical methods. We propose to process the next, more detailed level of pyramid only if the decision at the current level is ...
Added: December 4, 2015
Baibikova T., Качество. Инновации. Образование 2015 № 9 С. 25–28
The method for finding some geometric characteristics of objects in images is proposed. The method is intended to find the presence of some characteristic of the objects in images without expensive computations and refer the images to some definite classes. ...
Added: October 23, 2015