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Determining the location of objects using inertial sensors in mobile devices
Education - Technology - Computer Science. 2012. P. 265–275.
The article is devoted to questions of development of inertial navigation system for handheld devices and development of navigation algorithms on the basis of using accelerometers and gyroscopes in a mobile phone to track the movement of a walking person.
Language:
English
Митянов З. О., Законодательство 2026 № 4 С. 27–32
Modern technological tools not only make human life more comfortable but also entail numerous risks. The article highlights potential problems associated with the processing of biometric personal data by mobile devices, provides a legal assessment of access control based on biometric sensors, and examines the processing of biometric data in popular mobile applications. The author ...
Added: May 6, 2025
Savchenko A., Maslov D., Makarov I., , in: ECAI 2024. 27th European Conference on Artificial Intelligence, October 19 – 24 October 2024, Santiago de Compostela, Spain – Including 13th Conference on Prestigious Applications of Intelligent Systems (PAIS 2024).: IOS Press, 2024. P. 4439–4442.
Added: February 15, 2025
Makarov S., М.: ДМК Пресс, 2023.
Книга состоит из двух частей, содержащих как теоретические, так и практические сведения о работе с платами Arduino Uno и Raspberry Pi 3 или 4.
Первая часть посвящена теории и решению 23 практических заданий для Arduino Uno в среде Arduino IDE с большинством датчиков, модулей и других компонентов соответствующего набора с RFID-модулем, и предназначена для изучения как ...
Added: February 15, 2024
Savchenko A., Savchenko L., Makarov I., IEEE Access 2023 Vol. 11 P. 65977–65990
This paper addresses the face recognition task for offline mobile applications. Using AutoML techniques, a novel technological framework is proposed to develop a fast neural network-based facial feature extractor for a concrete device. First, the Once-for-All SuperNet is trained on a large facial dataset. Each device is characterized by its lookup table, which contains the ...
Added: August 28, 2023
Borisova M. D., Tomchuk K. K., A. M. Turlikov, , in: 2020 Wave Electronics and its Application in Information and Telecommunication Systems (WECONF).: IEEE, 2020. Ch. 9131479 P. 1–4.
The work considers a method for determining average relative difference in the length of the left and right legs' steps when walking on straight even surface. This value indirectly characterizes the degree of a number of diseases of the musculoskeletal and central nervous systems. The measurement interval for the difference in duration by the proposed ...
Added: October 31, 2022
Savchenko A., Savchenko L., Makarov I., IEEE Transactions on Affective Computing 2022 Vol. 13 No. 4 P. 2132–2143
In this paper, behaviour of students in the e-learning environment is analyzed. The novel pipeline is proposed based on video facial processing. At first, face detection, tracking and clustering techniques are applied to extract the sequences of faces of each student. Next, a single efficient neural network is used to extract emotional features in each ...
Added: July 14, 2022
Demochkina P., Savchenko A., , in: 2021 International Conference on Information Technology and Nanotechnology (ITNT).: IEEE, 2021. P. 1–5.
In this paper, we propose to solve the problem of facial expression recognition in videos by implementing a two-stage procedure, in which, firstly, facial features are extracted from all frames using an EfficientNet-based model. The latter is pre-trained to identify facial attributes and further fine-tuned on an external dataset for the emotion classification task. Secondly, ...
Added: April 10, 2022
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
Savchenko A., Demochkin K., Grechikhin I., Pattern Recognition 2022 Vol. 121 Article 108248
In this paper, a user modeling task is examined by processing mobile device gallery of photos and videos. We propose a novel engine for preferences prediction based on scene recognition, object detection and facial analysis. At first, all faces in a gallery are clustered, and all private photos and videos with faces from large clusters ...
Added: August 19, 2021
Grachev A., Ignatov D. I., Savchenko A., Applied Soft Computing Journal 2019 Vol. 79 P. 354–362
Recurrent neural networks have proved to be an effective method for statistical language modeling. However, in practice their memory and run-time complexity are usually too large to be implemented in real-time offline mobile applications. In this paper we consider several compression techniques for recurrent neural networks including Long–Short Term Memory models. We make particular attention ...
Added: June 12, 2019
Saleh H., Alexandrov D., Main problems of informatics and information education 2013 P. 264–267
The system of object positioning inside the building using mobile devices and points of Wi-Fi access is considered, in particular, its architecture and subsystem of working out of the building plans. ...
Added: October 20, 2015