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检索条件"任意字段=Conference on Algorithms, Devices, and Systems for Optical Information Processing"

共 3151 条记录，以下是71-80 订阅

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Estimating the Feasibility of Images Simulation in Unity 3D for Sub-Pixel processing algorithms

Estimating the Feasibility of Images Simulation in Unity 3D ...

引用

2023 Wave Electronics and its Application in information and Telecommunication systems, WECONF 2023

作者： Sivov, N. Yu. Shmatko, E.V. Poroykov, A. Yu. National Research University MPEI Department of Physics Named after V.A. Fabrikant Moscow Russia

ISBN: (纸本)9798350348293

Computer image simulation is used in the development of optical measurement systems and processing algorithms. It allows the performance of a system or algorithm to be verified and its measurement uncertainty to be assessed. Modern algorithms make it possible to achieve sub-pixel accuracy in digital image processing. An example of such algorithms is the cross-correlation processing in Particle Image Velocimetry. Often, standard graphics engines such as Unity 3D and Unreal Engine are used to simulate the images. The purpose of this work is to evaluate the possibility of using these tools to generate images for further processing by subpixel resolution algorithms. This paper presents the results of a computational experiment to estimate the maximum spatial resolution for simulations in Unity 3D. A qualitative and quantitative analysis of the results confirms the possibility of using the tested graphics engine for the analysis of subpixel resolution algorithms for digital image processing. © 2023 IEEE.

关键词： Engines

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Speech Command Recognition Algorithm Based on Improved MFCC Features

Speech Command Recognition Algorithm Based on Improved MFCC...

引用

International conference on Communications, Signal processing, and systems, CSPS 2023

作者： Song, Ziyi Ma, Lin School of Electronics and Information Engineering Harbin Institute of Technology Harbin China

ISBN: (纸本)9789819975396

In recent years, deploying low-power speech recognition algorithms on resource-constrained hardware devices has become a research focus. However, traditional algorithms rely on extensive data and complex models, which pose challenges for low-power devices with limited resources. This paper proposes an improved MFCC feature extraction method combined with the DTW algorithm, which enhances computational speed and reduces resource consumption in speech recognition. Experimental results validate the effectiveness and feasibility of the proposed method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Feature extraction

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Fed-FA: Theoretically Modeling Client Data Divergence for Federated Language Backdoor Defense 37

Fed-FA: Theoretically Modeling Client Data Divergence for Fe...

引用

37th conference on Neural information processing systems (NeurIPS)

作者： Zhang, Zhiyuan Chen, Deli Zhou, Hao Meng, Fandong Zhou, Jie Sun, Xu Peking Univ Sch Comp Sci Natl Key Lab Multimedia Informat Proc Beijing Peoples R China Tencent Inc WeChat AI Pattern Recognit Ctr Beijing Peoples R China

ISBN: (纸本)9781713899921

Federated learning algorithms enable neural network models to be trained across multiple decentralized edge devices without sharing private data. However, they are susceptible to backdoor attacks launched by malicious clients. Existing robust federated aggregation algorithms heuristically detect and exclude suspicious clients based on their parameter distances, but they are ineffective on Natural Language processing (NLP) tasks. The main reason is that, although text backdoor patterns are obvious at the underlying dataset level, they are usually hidden at the parameter level, since injecting backdoors into texts with discrete feature space has less impact on the statistics of the model parameters. To settle this issue, we propose to identify backdoor clients by explicitly modeling the data divergence among clients in federated NLP systems. Through theoretical analysis, we derive the f-divergence indicator to estimate the client data divergence with aggregation updates and Hessians. Furthermore, we devise a dataset synthesization method with a Hessian reassignment mechanism guided by the diffusion theory to address the key challenge of inaccessible datasets in calculating clients' data Hessians. We then present the novel Federated F-Divergence-Based Aggregation (Fed-FA) algorithm, which leverages the f-divergence indicator to detect and discard suspicious clients. Extensive empirical results show that Fed-FA outperforms all the parameter distance-based methods in defending against backdoor attacks among various natural language backdoor attack scenarios.

关键词： Natural language processing systems

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Fuzzy Morphological processing Algorithm of Blood Image 25

Fuzzy Morphological Processing Algorithm of Blood Image

引用

25th IEEE International conference of Young Professionals in Electron devices and Materials, EDM 2024

作者： Turgunov, Abrorjon M. Narzullaev, Temur N. Matyakubov, Marks Ya. Payzieva, Munira T. Kamolova, Sevara J. Rakhmonova, Nilufar N. Department of Algorithms and Mathematical Modeling Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan

ISBN: (纸本)9798350389234

This article, a morphological image processing algorithm is developed for early detection of viral hepatitis from microscopic blood images. It is mentioned that it can be used to accurately determine each boundary detail in the fuzzy morphological processing of the gray image of the blood image. Boundary detection leads to higher recognition results in neural network training. Compared to the work of a number of scholars, our method offers such performance, but it offers improved dynamics and flexibility in the formulation of linguistic boundary criteria, which can be a leading factor in the design of image processing systems with dynamic and flexible rules, such as Type 2 allows fuzzy rules, which offers an interesting alternative to currently common deep learning applications. The validated experimental results show the reliability of the modified method compared to the Chaira method. Mean, entropy and standard deviation were calculated. It turned out to be higher than the values of the Chaira method. © 2024 IEEE.

关键词： Neural networks

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Analysis of Application-Level Load Balancing algorithms

Analysis of Application-Level Load Balancing Algorithms

引用

2023 systems of Signals Generating and processing in the Field of on Board Communications, SOSG 2023

作者： Sukhoplyuev, D.I. Nazarov, A.N. Mirea Russian Technology University Institute of Information Technology Moscow Russia

ISBN: (纸本)9798350397727

The present article examines the application-level load balancing strategies employed in the microservice architecture of IoT servers, which use wireless communication protocols like Wi-Fi to exchange radio signals among IoT devices. Load balancing at the application level is a crucial task, add to address it, a hypothesis is proposed. To evaluate the effectiveness of various load balancing algorithms, mathematical models based on queuing theory are developed for four algorithms: Round Robin, Weighted Round Robin, Least Connection, and search of the optimal vector. A numerical analysis is conducted to compare the performance of these algorithms. The results confirm the aforementioned hypothesis, and highlight the need to develop a load balancing algorithm that can account for error coefficients arising from distinct services. © 2023 IEEE.

关键词： Numerical analysis

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Research on Improved TDOA Algorithm for Shallow Water Underwater Positioning 16

Research on Improved TDOA Algorithm for Shallow Water Underw...

引用

16th International conference on Signal processing systems, ICSPS 2024

作者： Shen, Biyue Rong, Shaowei Ji, Lingxian Wu, Kaiyuan Li, Jiaju Deng, Xiangyu Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Faculty of Artificial Intelligence Industry Kunming University of Science and Technology Kunming650500 China

ISBN: (纸本)9781510689251

Accurate positioning in shallow water regions is crucial for various underwater applications. TDOA algorithms estimate the signal source location by measuring the time differences of signal arrival at multiple receivers. However, these methods often suffer from Non-Line-of-Sight (NLOS) errors and noise, leading to reduced positioning accuracy in shallow water environments. This research proposes an improved TDOA estimation algorithm that utilizes cross-correlation techniques to mitigate NLOS errors and combines the strengths of the Chan and Taylor algorithms to enhance positioning precision. The proposed algorithm addresses challenges such as time ambiguity and alpha-stable noise, offering advantages in TDOA modeling for underwater positioning. Implementation details are provided, including the design of matching basis functions, time delay matching procedures, algorithm flow, and computational steps. Simulation tests validate the effectiveness of the algorithm, demonstrating significant improvements in positioning accuracy. The computational complexity is also analyzed to assess the algorithm's practicality. Finally, the research findings are summarized, and directions for future work are discussed. © 2025 SPIE.

关键词： Time difference of arrival

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Learning Optimal Edge processing with Offloading and Energy Harvesting 23

Learning Optimal Edge Processing with Offloading and Energy ...

引用

26th ACM International conference on Modelling, Analysis, and Simulation of Wireless and Mobile systems (MSWiM)

作者： Fox, Andrea De Pellegrini, Francesco Altman, Eitan Univ Avignon Lab Informat Avignon LIA Avignon France Univ Cote Azur INRIA Ctr Inria Sophia Antipolis France

ISBN: (纸本)9798400703669

Modern portable devices can execute increasingly sophisticated AI models on sensed data. The complexity of such processing tasks is data-dependent and has relevant energy cost. This work develops an Age of information markovian model for a system where multiple battery-operated devices perform data processing and energy harvesting in parallel. Part of their computational burden is offloaded to an edge server which polls devices at given rate. The structural properties of an optimal policy for a single device-server system are derived. They permit to define a new model-free reinforcement learning method specialized for monotone policies, namely Ordered Q-Learning, providing a fast procedure to learn the optimal policy. The method is oblivious to the devices' battery capacities, the cost and the value of data batch processing and to the dynamics of the energy harvesting process. Finally, the polling strategy of the server is optimized by combining this policy improvement technique with stochastic approximation methods. Extensive numerical results provide insight into the system properties and demonstrate that the proposed learning algorithms outperform existing baselines.

关键词： AoI Energy-Harvesting Offloading MDP Reinforcement Learning

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Intelligent Microbial Growth Monitoring: A Parallel OD600 Detection System Based on Artificial Intelligence 2

Intelligent Microbial Growth Monitoring: A Parallel OD600 De...

引用

2nd International conference on Machine Vision, Image processing and Imaging Technology, MVIPIT 2024

作者： Xu, Libing Ren, Fei Doma, Bonifacio T. Nanjing SuperKong Electronics Co. Ltd. Nan Jing China School of Information Technology Mapua University Philippines School of Graduate Studies Manila Philippines

ISBN: (纸本)9798331543037

Microbial OD600 measurement is a crucial experimental technique in microbiological and molecular biological research, evaluating microbial growth by measuring optical density at 600 nm wavelength. While convenient, this method has limitations. For instance, different microbial species and growth stages may absorb light differently, potentially leading to biases when measuring multiple strains simultaneously. This paper presents an innovative parallel OD600 detection system capable of simultaneously monitoring growth curves of multiple microbial strains. Our research integrates advanced optical systems, precise mechanical control, and artificial intelligence algorithms, not only improving the accuracy and efficiency of bacterial growth measurements but also achieving parallel processing and analysis of multiple samples. We discuss in detail the hardware design, software architecture, and core algorithms, with particular emphasis on the application of machine learning in multi-strain data analysis and prediction. Experimental results demonstrate that this system significantly outperforms traditional methods in measurement accuracy, automation level, multi-sample processing capability, and data analysis. ©2024 IEEE.

关键词： Bacteria

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Vehicle Number Plate Recognition And information Access System

Vehicle Number Plate Recognition And Information Access Syst...

引用

2024 International conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI, ICSCAI 2024

作者： Mane, Pradeep B. Patil, Varsha Kiran Paithankar, Mayur R. Kotgire, Mallikarjun M. Shah, Samveg S. Dept. Electronics and Telecommunication AISSMS Institute of Information Technology Pune India

ISBN: (纸本)9798350355338

Addressing the growing challenges posed by increasing vehicles and stringent traffic violations, many vehicle number plates go undetected while passing through toll booths and traffic lights. Thus it creates the need for a vehicle number plate recognition system. Existing systems employing ANPR algorithms utilize MATLAB and K-Nearest neighbour algorithms for image processing. Drawbacks include limitations in adapting to dynamic environments, Real time recognition, handling multiple vehicles, slow processing speeds, incapability of multiple object detection in single frame. The paper focuses on Automatic Number Plate Recognition (ANPR), employing specialized cameras and advanced image processing and using YOLOv8 for object detection and extracting license plate information from video feeds using EasyOCR. The noisy data generated during character recognition is filtered out using Regex based algorithm. The system integrates with centralized databases for real-time vehicle information access for users. The same database is used to automate e-challan updation, contributing to traffic management by swiftly issuing fines for rule violations. The proposed video-based processing system achieves number plate detection using YOLOv8 and storage of vehicle number plates in a centralized MongoDB database with an accuracy achieved of 96% in license plate detection and reduces noisy data using algorithm. It also enables real-time data retrieval through a user interface using Reactjs as frontend and is also connected to the MongoDB database for precise and user-friendly access in modern traffic systems. © 2024 IEEE.

关键词： optical character recognition

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Memory in Motion: Exploring Leaky Integration of Time Surfaces for Event-based Eye-tracking

Memory in Motion: Exploring Leaky Integration of Time Surfac...

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2024 Biomedical Circuits and systems conference

作者： Boretti, Chiara Bich, Philippe Prono, Luciano Pareschi, Fabio Royatti, Riccardo Setti, Gianluca Politecn Torino DET Turin Italy Politecnico Torino PiC4SeR Turin Italy Univ Bologna DEI Bologna Italy Univ Bologna ARCiS Bologna Italy KAUST CEMSE Thuwal Saudi Arabia

ISBN: (纸本)9798350354966;9798350354959

Augmented and Virtual Reality (AR/VR) technologies are gaining popularity to improve healthcare professionals training, with precise eye tracking playing a crucial role in enhancing performance. However, these systems need to be both low-latency and low-power to operate in real-time scenarios on resource-constrained devices. Event-based cameras can be employed to address these requirements, as they offer energy-efficient, high temporal resolution data with minimal battery drain. However, their sparse data format necessitates specialized processing algorithms. In this work, we propose a data pre-processing technique that improves the performance of nonrecurrent Deep Neural Networks (DNNs) for pupil position estimation. With this approach, we integrate over time - with a leakage factor - multiple time surfaces of events, so that the input data is enriched with information from past events. Additionally, in order to better distinguish between recent and old information, we generate multiple memory channels characterized by different leakage/forgetting rates. These memory channels are fed to well-known non-recurrent neural estimators to predict the position of the pupil. As an example, by using time surfaces only and feeding them to a MobileNet-V3L model to track the pupil in DVS recordings, we achieve a P10 accuracy (Euclidean error lower than ten pixels) of 85.40%, whether by using memory channels we achieve a P10 accuracy of 94.37% with a negligible time overhead.

关键词： information leakage

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