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42nd IEEE International Conference on computer Communications, INFOCOM 2023

作者： Tapolcai, Janos Babarczi, Peter Ho, Pin-Han Ronyai, Lajos Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Telecommunications and Media Informatics BudapestH-1111 Hungary University of Waterloo Deptartment of Electrical and Computer Engineering Canada Institute for Computer Science and Control Eötvös Loránd Research Networkand Department of Algebra Hungary Institute of Mathematics Budapest University of Technology and Economics BudapestH-1111 Hungary

ISBN: (纸本)9798350334142

Fast reroute (FRR) mechanisms that can instantly handle network failures in the data plane are gaining attention in packet-switched networks. In FRR no notification messages are required as the nodes adjacent to the failure are prepared with a routing table such that the packets are re-routed only based on local information. However, designing the routing algorithm for FRR is challenging because the number of possible sets of failed network links and nodes can be extremely high, while the algorithm should keep track of which nodes are aware of the failure. In this paper, we propose a generic algorithmic framework that combines the benefits of Integer Linear Programming (ILP) and an effective approach from graph theory related to constructive graph characterization of k-connected graphs, i.e., edge splitting-off. We illustrate these benefits through arborescence design for FRR and show that (i) due to the ILP we have great flexibility in defining the routing problem, while (ii) the problem can still be solved very fast. We demonstrate through simulations that our framework outperforms state-of-the-art FRR mechanisms and provides better resilience with shorter paths in the arborescences. © 2023 IEEE.

关键词： Graph theory

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An Approach to Formation control of UAVs Based on Applying Adapted Kohonen Neural Network

An Approach to Formation Control of UAVs Based on Applying A...

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Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT)

作者： Mikhail Khachumov Intelligent Control Laboratory Ailamazyan Program Systems Institute of RAS Pereslavl-Zalessky Russia Federal Research Center” Computer Science and Control” of RAS Moscow Russia

The paper gives a statement and considers the solution of an urgent scientific problem of formation control for a group of unmanned aerial vehicles (UAVs) operating in an unstable environment. To construct the reference trajectories and allocate UAVs to positions of a given structure, an original approach is proposed based on the adapted Kohonen neural network with a set of metrics, including Euclidean, Mahalanobis and Euclidean-Mahalanobis distances. To implement the movement of a UAV group in a complex environment, we apply the principles of intelligent-geometric control, which allows to combine flexible intelligent and precise geometric control methods within one concept. When moving along a given route, UAVs use a set of allowable control strategies. The developed modeling scheme is designed to take into account wind loads and possibly dangerous rapprochement of vehicles. To reflect the dynamics of UAVs, a special module is used that contains transfer functions integrated into a single stabilization system with an autopilot. The proposed approach has shown promise when simulating a series of formation control problems.

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Symbolic Disentangled Representations for Images

arXiv

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arXiv 2024年

作者： Korchemnyi, Alexandr Kovalev, Alexey K. Panov, Aleksandr I. Moscow Institute of Physics and Technology Dolgoprudny Russia AIRI Moscow Russia Federal Research Center "Computer Science and Control" Russian Academy of Sciences Moscow Russia

The idea of disentangled representations is to reduce the data to a set of generative factors that produce it. Typically, such representations are vectors in latent space, where each coordinate corresponds to one of the generative factors. The object can then be modified by changing the value of a particular coordinate, but it is necessary to determine which coordinate corresponds to the desired generative factor – a difficult task if the vector representation has a high dimension. In this article, we propose ArSyD (Architecture for Symbolic Disentanglement), which represents each generative factor as a vector of the same dimension as the resulting representation. In ArSyD, the object representation is obtained as a superposition of the generative factor vector representations. We call such a representation a symbolic disentangled representation. We use the principles of Hyperdimensional Computing (also known as Vector Symbolic Architectures), where symbols are represented as hypervectors, allowing vector operations on them. Disentanglement is achieved by construction, no additional assumptions about the underlying distributions are made during training, and the model is only trained to reconstruct images in a weakly supervised manner. We study ArSyD on the dSprites and CLEVR datasets and provide a comprehensive analysis of the learned symbolic disentangled representations. We also propose new disentanglement metrics that allow comparison of methods using latent representations of different dimensions. ArSyD allows to edit the object properties in a controlled and interpretable way, and the dimensionality of the object property representation coincides with the dimensionality of the object representation itself. © 2024, CC BY.

关键词： Vectors

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MAPF-GPT: Imitation Learning for Multi-Agent Pathfinding at Scale

arXiv

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arXiv 2024年

作者： Andreychuk, Anton Yakovlev, Konstantin Panov, Aleksandr Skrynnik, Alexey AIRI Moscow Russia Federal Research Center "Computer Science and Control" The Russian Academy of Sciences Moscow Russia Moscow Institute of Physics and Technology Dolgoprudny Russia

Multi-agent pathfinding (MAPF) is a problem that generally requires finding collision-free paths for multiple agents in a shared environment. Solving MAPF optimally, even under restrictive assumptions, is NP-hard, yet efficient solutions for this problem are critical for numerous applications, such as automated warehouses and transportation systems. Recently, learning-based approaches to MAPF have gained attention, particularly those leveraging deep reinforcement learning. Typically, such learning-based MAPF solvers are augmented with additional components like single-agent planning or communication. Orthogonally, in this work we rely solely on imitation learning that leverages a large dataset of expert MAPF solutions and transformer-based neural network to create a foundation model for MAPF called MAPF-GPT. The latter is capable of generating actions without additional heuristics or communication. MAPF-GPT demonstrates zero-shot learning abilities when solving the MAPF problems that are not present in the training dataset. We show that MAPF-GPT notably outperforms the current best-performing learnable MAPF solvers on a diverse range of problem instances and is computationally efficient during inference. © 2024, CC BY.

关键词： Zero-shot learning

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A Domain-Specific Multilingual Speech Translation Corpus via Simultaneous Interpretation

A Domain-Specific Multilingual Speech Translation Corpus via...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Han, Seunghee Lee, Gary Geunbae Kim, Hyung Soon Kim, Sunhee Chung, Minhwa Learning Sciences Research Institute Seoul National University Seoul Korea Republic of Department of Computer Science and Engineering Postech Pohang Korea Republic of Department of Electronics Engineering Pusan National University Busan Korea Republic of Department of French Language Education Seoul National University Seoul Korea Republic of Department of Linguistics Seoul National University Seoul Korea Republic of

ISBN: (纸本)9798350368741

This paper presents a novel multilingual speech translation corpus for complex, domain-specific content in Korean, English, Spanish, and Japanese. The corpus contains 4, 000 hours of parallel speech, including 1, 000 hours of Korean audio with simultaneous sight interpretations in the other three languages by 294 professionals (242 interpreters and 52 Korean voice actors). It also includes transcriptions, translations, and annotations for all languages. The Dewey Decimal Classification was adapted to balance knowledge representation, and speech tasks were conducted in a controlled studio environment to ensure data consistency. Translation, transcription, and annotation workflows were managed through a custom-built platform. The corpus captures nuanced contexts, cultural sensitivities, and domain-specific terminology, addressing linguistic challenges like structural differences between SOV (Korean, Japanese) and SVO languages (English, Spanish). Preliminary evaluations indicate its potential to enhance end-to-end speech translation models, support cross-lingual transfer learning, and tackle real-time translation issues. © 2025 IEEE.

关键词： Speech processing resources Speech recognition Speech synthesis Speech-to-speech translation

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Modeling and Simulation of Two Axes Gimbal Using Fuzzy control

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computers, Materials & Continua 2022年第7期72卷 93-107页

作者： Ayman A.Aly Mohamed O.Elhabib Bassem F.Felemban B.Saleh Dac-Nhuong Le Department of Mechanical Engineering College of EngineeringTaif UniversityTaif21944Saudi Arabia Control and Mechatronics Division School of Electrical EngineeringUTMJohor Bahru81300Malaysia Institute of Research and Development Duy Tan UniversityDanang550000Vietnam School of Computer Science Duy Tan UniversityDanang550000Vietnam

The application of the guided missile seeker is to provide stability to the sensor’s line of sight toward a target by isolating it from the missile motion and *** main objective of this paper is not only to present the physical modeling of two axes gimbal system but also to improve its performance through using fuzzy logic controlling *** paper is started by deriving the mathematical model for gimbals motion using Newton’s second law,followed by designing the mechanical parts of model using SOLIDWORKS and converted to xml file to connect dc motors and sensors using MATLAB/***,a Mamdani-type fuzzy and a Proportional-Integral-Derivative(PID)controllers were designed using MATLAB *** performance of both controllers was evaluated and tested for different types of input *** simulation results showed that self-tuning fuzzy controller provides better performance,since no overshoot,small steady-state error and small settling time compared to PID controller.

关键词： Gimbal system self-tuning fuzzy proportional-integral-derivative(PID)control cross coupling

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Privacy-protected object detection through trustworthy image fusion

Privacy-protected object detection through trustworthy image...

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作者： Zhang, Chao Zhang, Jinmei Yun, Lijun Zhang, Jun Su, Junbo Yunnan Key Laboratory of Optoelectronic Information Technology Yunnan Normal University Kunming China School of Physics and Electronic Information Yunnan Normal University Kunming China Engineering Research Center of Computer Vision and Intelligent Control Technology Department of Education of Yunnan Province Yunnan Normal University Kunming China Kunming Institute of Physics Ordnance Science and Research Academy of China Kunming China

The neural network-based technologies have emerged as a potent method for image fusion, object detection, and other computer vision tasks as the rapid development of deep learning. Multi-band infrared images, in particular, capture a more extensive range of radiation details and information compared to conventional single-band infrared images. Consequently, the fusion of multi-band infrared images can provide more features for object detection. However, it is crucial to consider that infrared images may contain sensitive information, potentially leading to privacy concerns. Ensuring datasets privacy protection plays a crucial role in the fusion and tracking process. To address both the need for improved detection performance and the necessity for privacy protection in the infrared environment, we proposed a procedure for object detection based on multi-band infrared image datasets and utilized the transfer learning technique to migrate knowledge learned from external infrared data to internal infrared data, thereby training the infrared image fusion model and detection model. The procedure consists of several steps: (1) data preprocessing of multi-band infrared images, (2) multi-band infrared image fusion, and (3) object detection. Standard evaluation metrics for image fusion and object detection ensure the authenticity of the experiments. The comprehensive validation experiments demonstrate the effectiveness of the proposed procedure in object detection tasks. Furthermore, the transfer learning can train our datasets and update the model without exposing the original data. This aspect of transfer learning is particularly beneficial for maintaining the privacy of multi-band infrared images during the fusion and detection processes. © 2024 John Wiley & Sons Ltd.

关键词： Object detection

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Multimodal Interface Architecture for Unmanned Aerial Vehicle control

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Russian Aeronautics 2022年第3期65卷 498-506页

作者： Abramov, N.S. Emel’yanova, Yu. G. Talalaev, A.A. Fralenko, V.P. Khachumov, M.V. Ailamazyan Program Systems Institute Russian Academy of Sciences ul. Petra Pervogo 4a Pereslavskii raion Yaroslavskaya oblast s. Ves’kovo152020 Russia Federal Research Center "Computer Science and Control" ul. Vavilova 44 Moscow119333 Russia

Abstract: We considered an approach to the construction of a combined smart interface for the control system of a quadrocopter-type unmanned aerial vehicle that integrates various methods of information input, processing, and transmission. In this work, the architecture and system of voice and gesture commands of the quadrocopter control system multimodal interface are presented. Training samples were prepared and experimental verification of recognition algorithms using artificial neural networks of deep learning was carried out. © 2022, Allerton Press, Inc.

关键词： Network architecture

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uSF: Learning Neural Semantic Field with Uncertainty

arXiv

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arXiv 2023年

作者： Skorokhodov, V.S. Drozdova, D.M. Yudin, Dmitry A. Moscow Institute of Physics and Technology Moscow Russia Moscow Russia Federal Research Center "Computer Science and Control" Moscow Russia

Recently, there has been an increased interest in NeRF methods which reconstruct differentiable representation of three-dimensional scenes. One of the main limitations of such methods is their inability to assess the confidence of the model in its predictions. In this paper, we propose a new neural network model for the formation of extended vector representations, called uSF, which allows the model to predict not only color and semantic label of each point, but also estimate the corresponding values of uncertainty. We show that with a small number of images available for training, a model that quantifies uncertainty performs better than a model without such functionality. Code of the uSF approach is publicly available at https://***/sevashasla/usf/. © 2023, CC BY.

关键词： Neural network models

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Single photon flux imaging with sub-pixel resolution by motion compensation 17

Single photon flux imaging with sub-pixel resolution by moti...

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Advanced Photon Counting Techniques XVII 2023

作者： Laurenzis, Martin Bacher, Emmanuel Seets, Trevor Ingle, Atul Velten, Andreas Christnacher, Frank French-German Research Institute of Saint-Louis 5 Rue du General Cassagnou Saint-Louis68301 France Department of Electrical and Computer Engineering University of Wisconsin-Madison MadisonWI53706 United States Department of Computer Science Portland State University PortlandOR97201 United States Department of Biostatistics and Medical Informatics University of Wisconsin-Madison MadisonWI53706 United States

ISBN: (纸本)9781510661387

Single photon counting avalanche diodes (SPADs) are versatile sensors for active and time-correlated measurements such as ranging and fluorescence imaging. These detectors also have great potential for passive or uncorrelated imaging. Recently, it was demonstrated that passive imaging of photon flux is possible by determining the mean photon arrival time. For ambient light illumination, timestamp data can be interpreted as a metric for the photon impingement rate. Various applications have been investigated including high-dynamic-range imaging, single-photon imaging, and capture of fast-moving objects or dynamic scenes. However, the appearance of noise and motion blur requires sophisticated signal processing that enables sub-pixel resolution imaging and reconstruction of the scene by motion compensation. In this paper, we present new results on the evaluation of global scene motion. In our approach, motion is intentionally generated by a rotating wedge prism, resulting in continuous global motion on a circular path. We have studied scenes with different optical contrast. © 2023 SPIE.

关键词： Avalanche diodes

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