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Детектирование эмоций в мультимедиа контенте
С. 852-857.
А. С. Попова, А. Г. Рассадин, А. А. Пономаренко
In this paper we consider the automatic emotions recognition problem, especially the case of digital audio signal processing. We consider and verify an approach in which the classification of a sound fragment is reduced to the problem of image recognition. The waveform and spectrogram are used as a visual representation of the image. The computational experiment was done based on Radvess open dataset including 8 different emotions: "neutral", "calm", "happy," "sad," "angry," "scared", "disgust", "surprised". The best accuracy result was 64%, which was produced by a combination of “|spectrogram + convolution neural network VGG-11”
Popova A. S., Alexandr G. Rassadin, Alexander A. Ponomarenko, , in : Advances in Neural Computation, Machine Learning, and Cognitive Research. Selected Papers from the XIX International Conference on Neuroinformatics, October 2-6, 2017, Moscow, Russia. Vol. 736.: Cham : Springer, 2017. P. 117-124.
In this paper we consider the automatic emotions recognition problem, especially the case of digital audio signal processing. We consider and verify an straight forward approach in which the classification of a sound fragment is reduced to the problem of image recognition. The waveform and spectrogram are used as a visual representation of the image. ...
Added: October 18, 2017
Churaev E., Savchenko A., , in : 2021 International Russian Automation Conference (RusAutoCon). : IEEE, 2021. P. 633-638.
In this paper, we examine the issue of video-based facial emotion recognition algorithms which show excellent performance on some benchmarks, but have much worse accuracy in practical applications. For example, the typical error rate of contemporary deep neural networks on the RAVDESS dataset is less than 5%. We argue that such results are obtained only ...
Added: October 7, 2021
Savchenko L., Информационные технологии 2020 Т. 26 № 5 С. 290-296
article deals with the problem of isolated words recognition based on deep convolutional neural networks. The use of
existing recognition systems in practice is limited by an insufficiently high degree of their reliability functioning in conditions of intense acoustic noise, such as street noise, sounds from passing vehicles, etc. Nowadays, the most accurate recognition methods are characterized by ...
Added: September 2, 2020
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
Kharchevnikova A., Savchenko A., В кн. : Сборник трудов IV Международной конференции и молодёжной школы "Информационные технологии и нанотехнологии" (ИТНТ 2018). : Самара : Предприятие "Новая техника", 2018. Гл. 124. С. 916-924.
In this paper we examine the age and gender video-based recognition problem using deep convolutional neural networks. The comparative analysis of classifier fusion algorithms to aggregate decisions for individual frames is presented. In order to improve the age and gender identification accuracy we implement the video-based recognition system with several aggregation methods. We provide the ...
Added: October 18, 2018
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
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
Vu T., Osokin A., Laptev I., , in : Proceedings of the IEEE International Conference on Computer Vision (ICCV 2015). : Santiago de Chile : IEEE, 2015. P. 2893-2901.
Person detection is a key problem for many computer vision tasks. While face detection has reached maturity, detecting people under full variation of camera view-points, human poses, lighting conditions and occlusions is still a difficult challenge. In this work we focus on detecting human heads in natural scenes. Starting from the recent R-CNN object detector, ...
Added: October 19, 2017
Solovyev R. A., Vakhrushev M., Radionov A. et al., , in : 2020 IEEE 40th International Conference on Electronics and Nanotechnology (ELNANO). : IEEE, 2020. Ch. 9088863. P. 688-693.
Automatic classification of sound commands is becoming increasingly important, especially for embedded and mobile devices. Many of these devices contain both microphones and cameras. The manufacturers that develop and produce them would like to use the same methodology for sound and image classification tasks. It’s possible to achieve by representing sound commands as images, and ...
Added: September 19, 2020
A. G. Rassadin, A. V. Savchenko, , in : CEUR Workshop Proceedings. Vol. 1901: Proceedings of the International conference Information Technology and Nanotechnology. Session Image Processing, Geoinformation Technology and Information Security.: CEUR-WS, 2017. P. 207-213.
In this paper, we consider the problem of insufficient runtime and memory space complexities of deep convolutional neural networks for visual emotion recognition. A survey of recent compression methods and efficient neural networks architectures is provided. We experimentally compare the computational speed and memory consumption during the training and the inference stages of such methods ...
Added: October 17, 2017
Tsvetkovskaya I. I., Tekutieva N. V., Prokofyeva E. N. et al., , in : 2020 Moscow Workshop on Electronic and Networking Technologies (MWENT). : IEEE, 2020. P. 1-5.
The availability of high-resolution satellite images obtained through space radio communications offers the opportunity to use the most advanced technologies and techniques for analyzing remote sensing data. The paper discusses the data obtained with the use of ground-based, airborne or space-based filming equipment, which makes it possible to obtain images in one or several sections ...
Added: June 23, 2020
Demochkina P., Savchenko A., , in : Pattern Recognition. ICPR International Workshops and Challenges. Virtual Event, January 10–15, 2021, Proceedings, Part V. : Springer, 2021. P. 266-274.
In this paper, we address the emotion classification problem in videos using a two-stage approach. At the first stage, deep features are extracted from facial regions detected in each video frame using a MobileNet-based image model. This network has been preliminarily trained to identify the age, gender, and identity of a person, and further fine-tuned ...
Added: April 10, 2022
Nikolaev K., Malafeev A., , in : Analysis of Images, Social Networks and Texts. 7th International Conference AIST 2018. : Springer, 2018. Ch. 12. P. 121-126.
This paper deals with automatic classification of questions in the Russian language. In contrast to previously used methods, we introduce a convolutional neural network for question classification. We took advantage of an existing corpus of 2008 questions, manually annotated in accordance with a pragmatic 14-class typology. We modified the data by reducing the typology to ...
Added: February 15, 2019
Babenko A., Slesarev A., Chigorin A. et al., , in : Lecture Notes in Computer Science. Proceedings of the 13th European Conference on Computer Vision (ECCV 2014). * 1. Vol. 8689.: Zürich : Springer, 2014. P. 584-599.
It has been shown that the activations invoked by an image within the top layers of a large convolutional neural network provide a high-level descriptor of the visual content of the image. In this paper, we investigate the use of such descriptors (neural codes) within the image retrieval application. In the experiments with several standard ...
Added: October 1, 2014
Malafeev A., Nikolaev K., , in : Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Kazan, Russia, July 17–19, 2019, Revised Selected Papers. Communications in Computer and Information Science. Vol. 1086.: Springer, 2020. P. 154-159.
In this paper, a deep learning method study is conducted to solve a new multiclass text classification problem, identifying user interests by text messages. We used an original dataset of almost 90 thousand forum text messages, labeled for ten interests. We experimented with different modern neural network architectures: recurrent and convolutional, as well as simpler ...
Added: November 7, 2019
A.D. Sokolova, A.V. Savchenko, , in : CEUR Workshop Proceedings. Vol. 2210: Proceedings of the International Conference Information Technology and Nanotechnology. Session Image Processing and Earth Remote Sensing .: [б.и.], 2018. P. 243-250.
In this paper we propose to organize information in video surveillance systems by grouping the video tracks, which contain identical faces. Aggregation of the features of individual frames extracted using deep convolutional neural networks are used in order to obtain a descriptor of video track. The tracks with identical faces are grouped using the known ...
Added: November 5, 2018
Криницкий М. А., Verezemskaya P., Гращенков К. В. et al., Atmosphere 2018 Vol. 9 No. 426 P. 1-23
Polar mesocyclones (MCs) are small marine atmospheric vortices. The class of intense MCs, called polar lows, are accompanied by extremely strong surface winds and heat fluxes and thus largely influencing deep ocean water formation in the polar regions. Accurate detection of polar mesocyclones in high-resolution satellite data, while challenging, is a time-consuming task, when performed ...
Added: November 26, 2020
Новиков О. В., Прикладная информатика 2013 № 5(47) С. 29-34
This article represents different techniques for building fast recommender systems based on dimension reduction and classification of web-site usage data. Description of different web-site types that use recommender systems is provided. ...
Added: October 28, 2013
Lobacheva E., Chirkova N., Vetrov D., / International Conference on Machine Learning. Series 1 "Workshop on Learning to Generate Natural Language". 2017.
Recurrent neural networks show state-of-the-art results in many text analysis tasks but often require a lot of memory to store their weights. Recently proposed Sparse Variational Dropout (Molchanov et al., 2017) eliminates the majority of the weights in a feed-forward neural network without significant loss of quality. We apply this technique to sparsify recurrent neural ...
Added: October 19, 2017
Lipatov M., Вестник Московского университета. Серия 1: Математика. Механика 2013 № 2 С. 39-42
We classify complex linear cocycles over ergodic automorphisms with the help of the barycenter method. A conjugating random matrix is built in explicit form. ...
Added: April 19, 2013
[б.и.], 2017
The performance of machine learning methods is heavily dependent on the choice of data representation (or features) on which they are applied. The rapidly developing field of representation learning is concerned with questions surrounding how we can best learn meaningful and useful representations of data. We take a broad view of the field and include ...
Added: October 31, 2018
Феста Ю. Ю., Воробьев И. А., Model Assisted Statistics and Applications 2022 Vol. 17 No. 1 P. 41-49
We currently see a large increase in e-commerce sector; it is becoming a central trend in the banking industry. Fraudsters keep up with modern technologies, and use weak points in human psychology and security systems to steal money from regular users. To ensure the required level of security, banks began to apply artificial intelligence in ...
Added: April 13, 2022
Kotlyarevskaya I. V., Knyazeva E. G., Yuzvovich L. I. et al., Integration of Education 2018 Vol. 22 No. 1 P. 8-24
Introduction: the networking as a development practice in business has not yet become widespread. Moreover, there are very few studies of network interactions in the field of science and education. Advances in marketing evaluation of network entities are very rare. The goal of this article is to develop methodological criteria for such an assessment. These ...
Added: October 31, 2019
Koch S., Matveev A., Jiang Z. et al., , in : Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2019). : IEEE, 2019. P. 9601-9611.
We introduce ABC-Dataset, a collection of one million Computer-Aided Design (CAD) models for research of geometric deep learning methods and applications. Each model is a collection of explicitly parametrized curves and surfaces, providing ground truth for differential quantities, patch segmentation, geometric feature detection, and shape reconstruction. Sampling the parametric descriptions of surfaces and curves allows ...
Added: November 26, 2019