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

共 3200 条记录，以下是231-240 订阅

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A New Traffic Prediction Algorithm with Machine Learning for optical Fiber Communication System 3

A New Traffic Prediction Algorithm with Machine Learning for...

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3rd IEEE Asian conference on Innovation in Technology, ASIANCON 2023

作者： Malhotra, Abhiraj Chitkara University Institute of Engineering and Technology Chitkara University Centre for Interdisciplinary Research in Business and Technology Punjab India

ISBN: (纸本)9798350302288

optical Fiber Communication systems are increasingly used for transport networks due to the low cost, large capacity, and high bit rate of optical transmission [1]. However, effective traffic management and predicting future congestion levels is a critical challenge in order to ensure smooth and reliable operations. Machine learning algorithms can be used to accurately predict the future traffic volumes in such networks, providing real-time information on expected capacity usage and allowing operators to take proactive measures to prevent congestion. In this paper, we propose a novel Machine Learning based traffic prediction algorithm for optical Fiber Communications systems (OFCSs). The proposed algorithm uses a combination of Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) architectures for predicting future traffic patterns. We train the model using a sequence of historical traffic data from an OFCS and evaluate it against benchmarks in terms of prediction accuracy and processing time. The results show that the proposed algorithm can make accurate traffic predictions, with a mean absolute error (MAE) of 0.036 for one-step-ahead predictions and 0.077 for five-steps-ahead. Furthermore, the processing time is significantly less than other benchmark models, providing a practical and reliable approach for predicting future traffic in OFCSs. We also discuss the implications of this study in terms of improving optical fiber capacity utilization and meeting the increased demand of growing data traffic. © 2023 IEEE.

关键词： optical fibers

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Real Time Monitoring and Prediction of Electromagnetic Compatibility Over Internet of Medical Things Using Kalman Filter Algorithm 17

Real Time Monitoring and Prediction of Electromagnetic Compa...

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17th International conference on Signal processing and Communication systems, ICSPCS 2024

作者： Hwata, Chiedza Armando, Egas José Gatera, Omar Rushingabigwi, Gerard Twizere, Celestin Mtonga, Kambombo Kigali Rwanda Eduardo Mondlane University Superior Rural School of Rural Development Mozambique Kigali Rwanda Rwanda Polytechnic Department of Information and Communication Technology Kigali Rwanda

ISBN: (纸本)9798350389630

The Internet of Medical Things has emerged as a transformative technology in healthcare, facilitating remote monitoring and management of medical devices. However, despite these benefits, there is a need for more vigilance in ensuring electromagnetic compatibility within the Internet of Medical Things networks. It is quite essential to prevent electromagnetic interference as it could compromise device efficacy and consequently patient safety. This study aims to enhance real-time detection and prediction of electromagnetic radiations on the Internet of Medical Things networks by leveraging the predictive capabilities of the Kalman filter. An experiment was conducted over 30 days to evaluate the performance of the algorithm in optimizing electromagnetic compatibility management thus mitigating electromagnetic interference events. The algorithm was implemented and validated with 2500 samples of radiation emissions, with coordinates of the device's location. The results indicated that the implementation of Kalman filter algorithms could reduce sensor noise by up to 88% of accuracy. This research contributes to advancing electromagnetic compatibility monitoring techniques on the Internet of Medical Things networks, offering valuable implications for the design and implementation of resilient healthcare systems. © 2024 IEEE.

关键词： Kalman filters

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Number Plate Recognition Using optical Character Recognition (OCA) and Connected Component Analysis (CCA) 1

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5th International conference on Smart Technologies in Data Science and Communication, SMART-DSC 2022

作者： Ramya, Puppala Chowdary, Tummala Haswanth Teja, Pisupati Krishna Hrushikesh, Tadepally Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Guntur India

ISBN: (数字)9789811968808

ISBN: (纸本)9789811968792

The number of automobiles has expanded dramatically during the last few decades. As a result, tracking them became extremely difficult. In the event of a traffic ticket or excessive speeding, identifying the automobile owner has become nearly impossible. Image processing was used to identify car license plates to make this practicable. That license plates will be retrieved from collected photographs utilizing perception and computer vision algorithms, and then we will utilize OCR information to recognize the license number. OCR stands for optical character recognition. We employ cameras to record high-speed photos of number plates for image recognition, and image processing algorithms to identify and validate the sequence of characters, as well as to convert the number plate image to text. We now utilize number plate recognition (NPR) to detect license plates. NPR is a computer vision technique that enables equipment to scan license plates on automobiles swiftly and automatically without the need for human intervention. Image processing methods include Hidden Markov models, linear filtering, neural networks, and others. Our goal here is to recognize license plates so that we can readily follow automobiles in the event of a traffic penalty or excessive speeding. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Character segmentation Number plate recognition (NPR) Recognized characters Vehicle number plate

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Design and Implementation of Personal Smart Home System Based on Edge Computing Gate 5

Design and Implementation of Personal Smart Home System Base...

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5th International conference on Computer Engineering and Intelligent Control, ICCEIC 2024

作者： Xu, Fangqin Jiang, Yue Yang, Shun Liu, Yixuan Shanghai Publishing and Printing College Department of Information and Intelligent Engineering Shanghai China College of Communication and Art Design University of Shanghai for Science and Technology Shanghai China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai China

ISBN: (纸本)9798331507992

With the advancements in IoT technology, cloud computing, and big data technology, smart living has become an integral part of people's lives. However, traditional intelligent data computing relies heavily on cloud services, which often suffer from issues such as slow response times and high energy consumption. To address these issues, this study introduces an edge computing architecture centered on gateways, serving as an intermediate layer between user devices and cloud servers. This architecture enables high-speed data processing, low-latency responses, and rapid end-to-end connections, making it suitable for most small-scale and personal smart home systems. © 2024 IEEE.

关键词： Smart homes

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Learning from synthetic data for object detection on aerial images

Learning from synthetic data for object detection on aerial ...

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2024 International conference on Image, Signal processing, and Pattern Recognition, ISPP 2024

作者： Guo, Chao Yu, Yinhui Huang, Jinze College of Communication Engine Jilin University Jilin Changchun China College of Information Management Minnan Institute of Technology Fujian Shishi China Jilin Provincial Radio and Television Station Jilin Changchun China

ISBN: (纸本)9781510680425

Camera-equipped Unmanned Aerial Vehicles (UAVs) have been developed as autonomous vision systems and are widely used in various fields such as surveillance, search and rescue, and agriculture. Object detectors need to be robust to changing light, weather, and different application scenarios in real-time applications. Object detection algorithms have evolved considerably in these years, however the performance of object detection for UAVs has lagged behind. As it is largely limited by the dataset. Obtaining manually labeled object detection datasets on UAVs is undoubtedly expensive, and requires comprehensive consideration of the UAV's position, the object's size, and the weather, etc. Meanwhile, UAVs are prohibited from flying in certain scenarios, and the collection of data also raises privacy issues. To address the above problems, this paper proposes a method to enhance the data based on the Unreal Engine (UE) and Airsim synthetic dataset. We also take a Generative Adversarial Network (GAN)-based domain adaptive approach to make reduce the domain difference between synthetic and real data. © 2024 SPIE.

关键词： Generative adversarial networks

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Low-loss Zero-index Waveguides and devices

Low-loss Zero-index Waveguides and Devices

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2024 conference on Lasers and Electro-Optics, CLEO 2024

作者： Dong, Tian Dai, Tianxiang Chen, Ye Liu, Yueyang Liu, Hancheng Wang, Yiting Ma, Anqi Hu, Haifeng Xu, Lihua Zhao, Le Chu, Weiguo Peng, Chao Wang, Jianwei Li, Yang State Key Laboratory of Precision Measurement Technology and Instrument Department of Precision Instrument Tsinghua University Beijing100084 China State Key Laboratory for Mesoscopic Physics School of Physics Peking University Beijing100871 China State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronics and Frontiers Science Center for Nano-optoelectronics Peking University Beijing100871 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China Nanofabrication Laboratory National Center for Nanoscience and Technology Beijing100190 China

We report flexible zero-index waveguides and devices whose loss is two orders of magnitude lower than the state of the art, enabling phase-error-free high-dense photonic integrated circuits for classical and quantum i... 详细信息

ISBN: (纸本)9781957171395

关键词： Photonic integrated circuits

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Design of polarimetric camera based on the single-layer twisted nematic liquid crystal device 12

Design of polarimetric camera based on the single-layer twis...

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SPIE 12th International Symposium on Multispectral Image processing and Pattern Recognition, MIPPR 2023

作者： Ye, Mao Zhu, Wenjie Liu, Kewei Zhang, Xinyu Institude of Artificial Intelligence Huazhong University of Science and Technology Hubei Wuhan430074 China National Key Laboratory of Science & Technology on Multispectral Information Processing Huazhong University of Science & Technology Wuhan430074 China School of Artificial Intelligence & Automation Huazhong University of Science & Technology Wuhan430074 China

ISBN: (数字)9781510674929

ISBN: (纸本)9781510674912

Polarization is the asymmetry of a light wave's electric field vibration direction with respect to its propagation direction, as a crucial clue for describing the light, which is one of the most apparent signs that distinguishes transverse waves from longitudinal waves. The current mainstream polarimetric cameras typically adopt a division of focal plane imaging architecture, in which a metal wire-grid structure is coupled with a detector to acquire the polarization state of the target. However, the structure of the division of focal plane reduces effective spatial resolution of the detector and requires complex registration algorithms to achieve pixel-level polarization acquisition, which leads to high equipment costs and impedes the development and application of polarimetric cameras in industrial production. In this paper, a single-layer twisted nematic liquid crystal (TNLC) is inserted to the imaging optical path of traditional camera to realize the polarization acquisition, allowing for a cost-effective transition from traditional devices to polarization imaging systems. The imaging detector coupled with the TNLC device can acquire polarization states ranging from 10 to 90-degree by adjusting the external voltage applied on the LC device. Moreover, a polarization angle calibration method based on a single-layer TNLC is proposed in this paper, providing a reliable reference for electrically controlled polarization angle acquisition. The experimental results acquired by presented imaging system demonstrate the feasibility and effectiveness of the proposed method. The TNLC based imaging scheme presented in this paper provides a solid foundation for developing simple, low-cost, and efficient polarimetric cameras. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Cameras

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Ultra-Low Energy 5G IoT devices with Updatable AI Models: A Dynamic AI-IoT Perspectives 2

Ultra-Low Energy 5G IoT Devices with Updatable AI Models: A ...

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2nd IEEE Global conference on Communications and information Technologies, GCCIT 2024

作者： Dhabliya, Dharmesh Yuvaraj, K. Chauhan, Rahul Sharma, Dikshit Kala Priyadarshini, G. Shankar Prasad, S. Vishwakarma Institute of Technology Department of Information Technology Pune India Karpagam Academy of Higher Education Department of Computer Science Coimbatore641021 India Graphic Era Hill University Uttarakhand Dehradun248002 India Graphic Era Deemed to be University Uttarakhand Dehradun248002 India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electrical and Electronics Engineering Chennai127 India School of Management - UG Management Karnataka Bangalore India

ISBN: (纸本)9798350388916

Ultra-Low-Power (ULP) Internet of Things (IoT) devices are becoming more important in the fast developing 5G and possible 6G networks, and this study tackles the problem of incorporating dynamic AI capabilities into these devices. We present the Dynamic AI-IoT design, a new framework that aims to do away with the tedium of firmware upgrades. This design makes use of Narrowband IoT (NB-IoT) to make cloud interactions run smoothly and includes specialized firmware modifications to make dynamic interactions with TinyML models possible. Many sectors rely on deep learning that is based on massive amounts of high-quality data. The information accumulation of the framework relies on real-time acquisitions, which makes it difficult to directly implement deep learning in a real-time system. But such systems' analytical activities can't be done by collecting data for a lengthy period since they need to be executed in real time. This research presents a novel progressive deep-learning architecture and performs experiments on picture identification to address the challenges of high-quality data collection, high-timeliness data processing, and the difficulties of directly integrating deep-learning algorithms in real-time systems. The experimental findings demonstrate the efficacy, performance, and ability to get a conclusion comparable to the deep-learning architecture using large-scale data. An advanced method for managing memory is presented for the effective handling of AI tasks;it is based on memory alignment and the dynamic resolution of AI activities. Through the use of ULP IoT gadgets on a 5G testbed, empirical investigations show that the implementation of a Dynamic AI-IoT network is feasible. With an average inference duration of around 46 ms and model updates averaging less than one second, the findings are impressive. © 2024 IEEE.

关键词： Firmware

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Selective preparation of high-performance Cu metal micropatterns based on laser direct writing technology 14

Selective preparation of high-performance Cu metal micropatt...

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14th International conference on information Optics and Photonics, CIOP 2023

作者： Xie, Xiaozhu Huang, Yajun Laser Micro/Nano Processing Lab School of Electromechanical Engineering Guangdong University of Technology Guangdong Guangzhou510006 China Department of Experiment Teaching Guangdong University of Technology Guangdong Guangzhou510006 China

ISBN: (纸本)9781510671744

In recent years, research interest has rapidly increased in the selective metallization of different substrate materials (flexible substrates and hard and brittle materials). Due to their unique optical and electrical properties, the fabrication of metal patterns on various substrate materials has a wide range of applications. These include micro-electro-mechanical systems, micro-heaters in micro-fluidic systems, electrodes for electronic devices and flexible wearable devices. However, the differences in the properties of the substrate materials themselves lead to poor adhesion of the metal micropatterns to their substrate materials, which is one of the main factors affecting the selective metallization of their surfaces. Therefore, a method for selective preparation of high-performance patterning is needed. Laser direct writing technology, as an emerging low-cost, high-efficiency and high-precision processing technology, can realize the preparation of fine metal selective patterning. This is significant for preparing optoelectronics and semiconductor micro/nanostructures and devices. This paper reviews the research progress related to the preparation of high-performance Cu metal micropatterning by laser direct writing, which mainly includes laser direct structuring, laser-induced selective activation, laser-induced selective reductive sintering of metal precursor nano-inks and laser-induced forward transfer. By reviewing the research of this group and the current related research results, the current research status of the preparation of selective metal patterning in different substrate materials is investigated and introduced from the fundamental mechanisms and process characteristics of the various methods. This paper can provide a reference for the research and application of high-performance Cu metal micropatterning prepared by laser direct writing. These high-performance metal micropatterns are useful for microcircuit defect repair, glass heating devices, and

关键词： Copper

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Algorithm for Preliminary processing Channel State information of the WIFI Communication Channel for Building Indoor Positioning systems 24

Algorithm for Preliminary Processing Channel State Informati...

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24th International conference on Digital Signal processing and its Applications, DSPA 2022

作者： Astafiev, A.V. Zhiznyakov, A.L. Zakharov, A.A. Privezentsev, D.G. Vladimir State University Department of Software Engineering Murom Russia

ISBN: (纸本)9781665494434

The work is devoted to the development of an algorithm for preprocessing channel state information of the WIFI communication channel for building indoor positioning systems. The relevance of the work is associated with the rapid growth of the market for mobile smart devices. The use of such devices requires higher positioning accuracy than existing methods and approaches can provide. In this regard, the problem solved in the framework of the study is an urgent scientific and technical problem. The paper proposes consideration of information about the channel state information, as opposed to the method of measuring the RSSI signal level, adopted in most radio positioning algorithms. Unlike RSSI, the link state information includes information about the signal transmitted on each of the subcarriers. The paper considers the WiFi4 standard with 56 sub carriers. The data packet contains information about the phase and amplitude of the signal. The study considers a technique for obtaining data on the channel state information, its collection, preprocessing and synchronization. The algorithms considered in the article make it possible to prepare initial, raw data for use in practical indoor positioning algorithms using data mining methods. © 2022 IEEE.

关键词： Channel state information

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