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检索条件"机构=Department of Electrotechnical and Computer Engineering"

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The Task of Localizing the Source of Air Pollution by a Group of Drones Using Multi-Agent Approach

The Task of Localizing the Source of Air Pollution by a Grou...

引用

2024 Conference of Young Researchers in Electrical and Electronic engineering, ElCon 2024

作者： Khassanov, Akmal M. Lazarev, Eduard A. Viksnin, Ilya I. Saint-Petersburg Electrotechnical University 'LETI' Department of Computer Engineering Saint-Petersburg Russia

ISBN: (纸本)9798350360646

The article discusses the solution to the problem of localizing a single source of air pollution using a group of drones using a multi-agent approach. A description of the algorithm for searching and localizing pollution in a given area is given. A special software platform has been developed to implement the algorithm and evaluate the results of its work. © 2024 IEEE.

关键词： group of drones localization of air pollution source multi-agent approach uav

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Methods of Visual Information Processing

Methods of Visual Information Processing

引用

2024 Conference of Young Researchers in Electrical and Electronic engineering, ElCon 2024

作者： Nikulin, Nikita O. Bekeneva, Yana A. Saint Petersburg Electrotechnical University 'LETI' Department of Computer Engineering Saint Petersburg Russia

ISBN: (纸本)9798350360646

Visual information processing is required in a large number of different fields of human activity. A large number of new methods and techniques for its performing appear with the development of information technology. The article discusses some methods of processing visual information that are suitable for solving various tasks. © 2024 IEEE.

关键词： 3D reconstruction classification compression image enhancement image processing image restoration segmentation visual information acquisition Visual information processing

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Method and Decision Support System on Redesign of LSI Cells Topology 27

Method and Decision Support System on Redesign of LSI Cells ...

引用

27th International Conference on Soft Computing and Measurements, SCM 2024

作者： Mironov, Sergej E. Vyachin, Aleksandr V. Saint Petersburg Electrotechnical University 'LETI' Department of Computer Engineering Saint Petersburg Russia

ISBN: (纸本)9798350363708

The paper describes the method and software developed by the authors to support decision-making for processing the topology of microelectronic objects. The software base on the system of criteria for the efficiency of integrated circuit topology design proposed by the authors. Scientific novelty lies in the development of monitoring and analysis tools that localize topological clusters that require redesign © 2024 IEEE.

关键词： Topology

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Accurate Anomaly Detection in Medical Images using Transfer Learning and Data Optimization: MRI and CT as Case Studies 5

Accurate Anomaly Detection in Medical Images using Transfer ...

引用

5th International Conference on Neural Networks and Neurotechnologies, NeuroNT 2024

作者： Nizamli, Yasser Filatov, Anton Yu. Fadel, Weaam Shichkina, Yulia A. Saint Petersburg Electrotechnical University 'LETI' Department of Software Engineering and Computer Applications Saint Petersburg Russia Saint Petersburg Electrotechnical University 'LETI' Department of Computer Science Saint Petersburg Russia

ISBN: (纸本)9798350363739

Today, medical imaging techniques are widely used to detect a variety of human conditions and diseases. To speed up the diagnostic process, systems are often automated using deep learning methods, which have been proven to yield outstanding results. However, these models may be limited to a specific domain, prone to overfitting, and difficult to update. In this paper, we present a transfer learning approach that achieves high accuracy for detecting anomalies in both MRI and CT images. Our system utilizes the ConvNeXt network, inspired by the Swin Transformer architecture, as a high-level feature extractor from processed and augmented medical images. The resulting data is then optimized using the Edited Nearest Neighbors algorithm, which selects the most effective observations and discards the rest. Finally, the data is passed to the K-Nearest Neighbors classifier to detect anomalies in numerically represented images. Our model achieves high performance for two different types of medical images and can easily be updated without the need for retraining. © 2024 IEEE.

关键词： Magnetic resonance imaging

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Hardware Implementation of the Multiplier Using Argument Bit Grouping 27

Hardware Implementation of the Multiplier Using Argument Bit...

引用

27th International Conference on Soft Computing and Measurements, SCM 2024

作者： Bureneva, Olga I. Pavlov, Alexander P. Saint Petersburg Electrotechnical University 'LETI' Department of Computer Science and Engineering Saint Petersburg Russia

ISBN: (纸本)9798350363708

The paper considers an approach to the construction of multipliers based on the combination of Vedic principles of multiplication and classical algorithm with summation of partial products using matrix architecture. The paper shows the algorithm realized by the multiplier, presents a variant of implementation of the multiplier with two-bit groupings of argument bits, estimates hardware costs and time characteristics of the obtained combinational and pipeline multipliers based on FPGA of Cyclone III family of IntelFPGA company. © 2024 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Improving the MPI Remote Memory Access Model for Distributed-memory Systems by Implementing One-sided Broadcast 27

Improving the MPI Remote Memory Access Model for Distributed...

引用

27th International Conference on Soft Computing and Measurements, SCM 2024

作者： Abuelsoud, Mohamed Paznikov, Aleksej A. Saint Petersburg Electrotechnical University 'LETI' Department of Computer Science and Engineering Saint Petersburg Russia

ISBN: (纸本)9798350363708

Currently, processing large volumes of expanding data efficiently and consistently is a significant challenge. Traditional distributed-memory high-performance computers (HPC) based on message-passing model struggle with inherent synchronization difficulties, limiting their ability to keep pace. Remote Memory Access (RMA, also known as one-sided MPI communications) allows a process to directly read from or write to the memory of another process, bypassing the need for message exchange. Unfortunately, there is no collective operation interface in the current MPI RMA standard. However, RMA has the potential to reduce synchronization costs by enabling concurrent access to shared data structures, distributed among MPI processes' memories. Existing onesided MPI standards offer a linear interface only that hampers parallelization and far from efficient. To bridge this gap, we propose an algorithm design for efficient collective (parallelizable) operations in the RMA paradigm. Our study primarily examines the benefits of collective operations using the broadcast algorithm as an example. Our implementations surpass traditional methods, demonstrating the promising potential of this technique, as more performance tests indicate. © 2024 IEEE.

关键词： Parallel programming

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Assessment of Human State Based on Data from Keyboard Activity 5

Assessment of Human State Based on Data from Keyboard Activi...

引用

5th International Conference on Neural Networks and Neurotechnologies, NeuroNT 2024

作者： Ma, Danting Saint Petersburg Electrotechnical University 'LETI' Department of Computer Science and Engineering Saint Petersburg Russia

ISBN: (纸本)9798350363739

In this study, we present a model developed for assessing human emotional states using data obtained from interactions with a computer keyboard. The model incorporates a feedback mechanism, which significantly enhances the accuracy of emotional state predictions. Through systematic analysis of the dynamics of keyboard usage by the user and monitoring individual environmental factors, our approach not only predicts the user's state but also adapts to changes in user behavior. The efficacy of the model was validated through conducted experiments. The model's ability to enhance adaptability to humans and the personalization of user interfaces improves human interaction with intelligent systems. The developed system demonstrates directions for improvements in human-machine interfaces, providing a foundation for future integration into more complex systems aimed at comprehensive assessment of psychophysiological states. © 2024 IEEE.

关键词： Machine learning

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Improving Transfer Learning Performance for Abnormality Detection in Brain MRI Images Using Feature Optimization Techniques 27

Improving Transfer Learning Performance for Abnormality Dete...

引用

27th International Conference on Soft Computing and Measurements, SCM 2024

作者： Nizamli, Yasser A. Filatov, Anton Yu. Saint Petersburg Electrotechnical University 'LETI' Department of Software Engineering and Computer Applications Saint Petersburg Russia

ISBN: (纸本)9798350363708

Accurate and early diagnosis of brain tumors plays a vital role in determining appropriate treatment and increasing survival rates. Manual diagnosis using MRI images is often prone to errors and can be a tedious and time-consuming procedure. As a result, automated computer-aided systems that utilize artificial intelligence and machine learning techniques are widely used. However, accurately diagnosing the type of brain tumor remains a significant and complex challenge for today's medical imaging research community. In this paper, we present an enhanced transfer learning approach that aims to differentiate brain tumor types using MRI scans while achieving state-of-the-art performance. In the proposed approach, the pre-trained VGG-19 network with fixed weights is used to map MRI scans to a high-level numerical representation. The extracted features are then passed to a support vector machine algorithm to classify brain tumors into one of three major categories: glioma, meningioma, and pituitary. To further improve the performance of the model, the effectiveness of utilizing feature optimization techniques based on the radial basis similarity function and L1-penalty logistic regression was investigated. For evaluation, the benchmark Figshare dataset containing 3064 MRI images was used after a series of processing operations. The proposed system achieved a high overall accuracy of 98.53%, outperforming other analogues. © 2024 IEEE.

关键词： Magnetic resonance imaging

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Federated Learning with Non Independent and Identically Distributed Data

Federated Learning with Non Independent and Identically Dist...

引用

2024 Conference of Young Researchers in Electrical and Electronic engineering, ElCon 2024

作者： Mreish, Kinda Kholod, Ivan I. Saint-Petersburg Electrotechnical University 'LETI' Computer Engineering Department Saint Petersburg Russia Saint-Petersburg Electrotechnical University 'LETI' Information Systems Department Saint Petersburg Russia

ISBN: (纸本)9798350360646

The aim of this article is to study the effect of different Federated Learning strategies with several non-IID (Independent and Identically Distributed) data distributions on the test accuracy of the studied neural network model and compare it with the centralized training. In this work, we focus on implementation of three Flower framework algorithms with four non-IID data skews to conduct classification of dumpers cases. The experiments show that the test accuracy in centralized training was up to 85 % while in decentralized case was up to 81%. © 2024 IEEE.

关键词： classification dumpers dataset federated learning strategies flower framework neural network model non-IID data distribution

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Two-branch Convolutional Networks for Stress Detection from Biomedical Data 27

Two-branch Convolutional Networks for Stress Detection from ...

引用

27th International Conference on Soft Computing and Measurements, SCM 2024

作者： Dobrokhvalov, Maksim O. Filatov, Anton Yu. Saint Petersburg Electrotechnical University 'LETI' Department of Software Engineering and Computer Applications Saint Petersburg Russia

ISBN: (纸本)9798350363708

Stress is considered one of the main causes of health problems. Combining physiological signals from multiple modalities is a promising method for more accurately determining a person's condition. This paper proposes single-branch and two-branch convolutional neural networks for stress detection using biomedical data (electrocardiogram, blood pulse pressure, electrodermal activity). The two-branch model independently processes heart data (electrocardiogram or blood volume pulse) and electrodermal activity, and then merges the results of the branches using a predictor. The work examines various predictors. In some predictors, only the final result of the network is transferred to the loss function, and in one, the results of each branch and the whole network are taken into account. On the WESAD dataset, the single-branch model achieves an accuracy 0.983 and an F1 score 0.976, and the two-branch model achieves an accuracy 0.994 and an F1 score 0.992. On the UBFC-Phys dataset, the single-branch model achieves an accuracy of 0.922 and an F1 score of 0.945. © 2024 IEEE.

关键词： Electrocardiograms

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