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

共 1192 条记录，以下是81-90 订阅

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A Parametric State-Space Network for Global Impairments Compensation in optical systems 15

A Parametric State-Space Network for Global Impairments Comp...

引用

15th International conference on Communications, COMM 2024

作者： Frunza, Alexandru Choqueuse, vincent Miron, Flavius Azou, Stephane Communications and Information Technology Military Technical Academy Bucharest050141 Romania Lab-STICC CNRS UMR 6285 École Nationale D'Ingénieurs de Brest France

ISBN: (纸本)9798350355956

This paper presents a novel compensation approach based on a parametric State-Space Network that aims to compensate for multiple linear imperfections in coherent optical communications. A communication impaired by residual in-phase/quadrature imbalance, chromatic dispersion, and laser phase noise is considered. The State-Space Network is composed of multiple parametric layers that mitigate the imperfections impact in a global manner. The proposed technique benefits from the augmentation of some conventional compensation algorithms by transforming some fixed parameters into learnable ones. For example, the phase noise compensation layer consists of an modified Kalman filter that has the ability to automatically update its process and observations noises, leading to a better resilience to improper initial tuning. The proposed method outperforms a conventional digital signal processing compensation scheme in certain scenarios, making it promising for future extensions. © 2024 IEEE.

关键词： Chromatic dispersion

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Adaptive analysis of rapid prediction of coal quality information based on image analysis

Adaptive analysis of rapid prediction of coal quality inform...

引用

2022 International conference on Computer Graphics, Artificial Intelligence, and Data processing, ICCAID 2022

作者： Liu, Ming Zhang, Hua CHN Energy Xinjiang Chemical Co. Ltd. Xinjiang Urumqi831404 China

ISBN: (纸本)9781510663350

Machine vision technology has shown great potential for development and application in the coal heat utilization and coal chemical production process It is important to carry out image analysis-based stability adaptation analysis of coal heat utilization and coal chemical equipment. To further expand its application, this work reviewed the characteristics of different vision sensor systems and image processing algorithms in the process of image acquisition and processing, conducted applicability analysis for rapid prediction of coal quality, presented the current problems and future development trends of image analysis technology in the coal heat utilization and coal chemical production process. It provided theoretical guidance and reference for promoting automation, intelligence, and mechanization in the coal industry. © 2023 SPIE.

关键词： Forecasting

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Study of motion delay correction algorithms in time synchronization

Study of motion delay correction algorithms in time synchron...

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2024 International conference on Mechatronic Engineering and Artificial Intelligence, MEAI 2024

作者： Liu, Xiaoyi Li, Jiayin Hu, Xiaoyang Ladimirovich, Perliuk Vladimir Shao, Yunzhuo College of Equipment Engineering Shenyang Ligong University Liaoning Province Shenyang110159 China Institute of Aerospace Instruments and Systems St. Petersburg University of Aerospace Instrumentation St. Petersburg190000 Russia Inner Mongolia First Machinery Group Co Ltd. Inner Mongolia Autonomous Region Baotou014030 China

ISBN: (纸本)9781510689176

As human exploration and research of science extends from the ground to deep space, for satellites with faster relative motion speeds and time information that is difficult to accurately obtain the time, this paper proposes a POLA motion delay correction algorithm, which only needs the motion speed of one of the two parties of time synchronization and the position information of both parties to correct the motion delay difference, so that the two-way time synchronization accuracy is not affected by the speed accuracy of the poorer party The algorithm only needs the velocity and position information of one of the time synchronization parties to correct the delay difference, so that the two-way time synchronization accuracy is not affected by the velocity error of the party with poor velocity accuracy. The effectiveness of the algorithm is verified through simulation tests. © 2025 SPIE.

关键词： Clocks Satellites Motion measurement Ranging Antennas Motion analysis Signal processing Aerospace engineering Kinematics Receivers

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Enhancing Vehicle Analysis with Fine Estimation on video Streams Using Image processing Techniques

Enhancing Vehicle Analysis with Fine Estimation on Video Str...

引用

2023 Annual International conference on Emerging Research Areas: International conference on Intelligent systems, AICERA/ICIS 2023

作者： Radha, R. Reddy, Kotha Bhargavi Yeshwanth, R. Alliance University Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350303452

Enhancing Vehicle Analysis with fine Estimation on video streams time object detection and tracking, and OCR for license plate recognition. By leveraging YOLO, the project extracts precise vehicle information from video streams, enabling comprehensive data collection for traffic analysis. Additionally, OCR algorithms automatically identify license plate numbers, facilitating law enforcement and fine estimation. This integrated approach enhances vehicle analysis, providing valuable insights for traffic optimization, infrastructure planning, and law enforcement strategies. The project aims to create safer, more efficient cities by harnessing the power of image processing techniques like YOLO and OCR in realtime vehicle analysis. © 2023 IEEE.

关键词： optical character recognition

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Research on intrusion detection method of party building network in colleges and universities based on machine learning

Research on intrusion detection method of party building net...

引用

2024 International conference on Signal processing and Communication Security, ICSPCS 2024

作者： Fan, Chaozhi Beijing Information Science and Technology University Beijing100192 China

ISBN: (纸本)9781510681699

The rapid development of the Internet and the intelligent information age have provided more possibilities for data leakage, network attacks and other behaviors of malicious persons. The network security of party building in colleges and universities faces severe challenges. Intrusion detection is a new information security technology used to detect intrusions in computer network systems. Intrusion detection methods based on machine learning can better identify unknown anomalies than rule-based methods. The essence of the intrusion detection problem is a classification problem. There are many classification methods in machine learning, including convolutional neural networks, naive Bayes, SVM, etc. These algorithms have good classification performance on balanced data sets. How to extract more representative attribute features from complex data sets to more accurately describe normal behavior and intrusion behavior has become an important breakthrough point in current intrusion detection solutions based on machine learning. In order to solve the problem of network intrusion for party building in universities, this paper proposes to apply the convolutional neural network algorithm and random forest algorithm in machine learning to the intrusion detection model of party building network in universities, which effectively improves the overall classification accuracy of the model and the recognition rate of minority classes. © 2024 SPIE.

关键词： Intrusion detection

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Hole repair of 3D terrain mesh in satellite stereo image reconstruction

Hole repair of 3D terrain mesh in satellite stereo image rec...

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2024 International conference on Remote Sensing, Mapping, and Geographic information systems, RSMG 2024

作者： Bao, Qiwei Liu, Jun Liu, Xining Zhao, Limin Yuan, Zhanliang Chen, Xingfeng Li, Jiaguo Li, Huafu Zhang, Haixiang School of Surveying and Land Information Engineering Henan Polytechnic University Jiaozuo454003 China Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China Sanya Institute of South China Sea Geology Guangzhou Marine Geological Survey China Geological Survey Sanya572024 China

ISBN: (纸本)9781510685826

When constructing a 3D surface grid using point cloud data closely matched with high-resolution satellite stereo images, holes often appear due to matching failures or limitations of triangulation algorithms, affecting the grid's integrity and the accuracy of subsequent applications. To solve this problem, a boundary contraction algorithm is studied for repairing mesh holes. The research focuses on different terrain conditions such as mountains, plains, and cities, and evaluates the effectiveness of boundary contraction algorithms in repairing holes. Using visual inspection methods, the quality of the repaired mesh is checked to ensure its integrity, smoothness, continuity, and topological correctness. The experimental results of GF-7 satellite images show that the boundary contraction algorithm can effectively fill holes in various terrain environments, significantly improving the geometric quality and overall integrity of the mesh, verifying its feasibility as a reliable mesh repair method, and providing strong support and verification for the application of the boundary contraction algorithm in actual terrain data processing. © 2024 SPIE.

关键词： Mesh generation

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Selection of Color Contrast Objects Against a Non-Stationary Background Using Modified HSV Model 6

Selection of Color Contrast Objects Against a Non-Stationary...

引用

6th IEEE International conference on information and Telecommunication Technologies and Radio Electronics, UkrMiCo 2023

作者： Popov, Anatoliy Vasilyeva, Irina Kosharskyi, Volodymyr Dergachov, Konstantin National Aerospace University Kharkiv Aviation Institute Department of Aerospace Radioelectronic Systems Kharkiv Ukraine National Aerospace University Kharkiv Aviation Institute Department of Information-Communication Technologies Named after O.O. Zelensky Kharkiv Ukraine National Aerospace University Kharkiv Aviation Institute Department of Aircraft Control Systems Kharkiv Ukraine

ISBN: (纸本)9798350348484

For the development of such smart systems based on the computer vision as, for example, unmanned aerial vehicles, driverless cars, etc. efficient image processing algorithms are required. These algorithms should provide the possibility to process images in a video stream, perform segmentation, select objects and define informative signatures for further recognition. Objects in optical images usually differ in color, shape, may have shadows, and they stand out against the non-stationary background of the terrain;that is why the HSV color model is often used for their selection. To select objects against the background of the terrain it is necessary to define their signatures and train the recognition system. However the variety of objects and the dependence of their color characteristics on changes in illumination pose a considerable problem. The paper proposes an alternative approach - to train the system to recognize the background, and the fragments of the image that are not recognized as the background should be classified as objects. For real-time estimation of the color parameters of the background it is proposed to convert the traditional HSV model into a one-dimensional signature to speed up calculations during processing. processing of the images received from an unmanned aerial vehicle by the proposed method makes it possible to select almost all objects of different colors, shapes and sizes against a heterogeneous background and to define their contours for further recognition. © 2023 IEEE.

关键词： Geometrical optics

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An Intrusion Detection Method Combining Bayesian Optimization and LightGBM

An Intrusion Detection Method Combining Bayesian Optimizatio...

引用

2023 International conference on algorithms, High Performance Computing, and Artificial Intelligence, AHPCAI 2023

作者： Xu, Dongyuan Hua, Bin School of Information Engineering Ningxia University Yinchuan China

ISBN: (纸本)9781510671881

Network is a double-edged sword, which brings great convenience and some risks at the same time. Then intrusion detection, as a proactive and defensive technical means, plays a very important role in protecting information systems. Traditional intrusion detection systems have the problems of low detection accuracy and poor real-time performance, while the existing network intrusion detection data is not balanced, so this paper proposes an adaptive synthesis algorithm (ADASYN) oversampling + class balancing data balancing algorithm and an intrusion detection method of LightGBM combined with Bayesian optimization algorithm, aiming to solve the above problems. First, data preprocessing we encode the data with labels as well as unique heat encoding to better pass into the model for processing, after that we increase a few classes of data by ADASYN oversampling to make the number of samples in each class relatively balanced, and finally the features are passed into LightGBM for learning and training, and finally validated in the NSL-KDD dataset for multi-class classification experiments, and the results show that Compared with other traditional algorithms, all data are improved and show better performance. © 2023 SPIE. All rights reserved.

关键词： Intrusion detection

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optical Character Recognition for Urdu Text: A Review of Techniques, Challenges, and Future Directions 5

Optical Character Recognition for Urdu Text: A Review of Tec...

引用

5th IEEE International conference on Advances in Electronics, Computers and Communications, ICAECC 2023

作者： Shaik, Moinuddin Ahmed Abdul, Wahid Maulana Azad National Urdu University Dept. of Computer Science and Information Technology Hyderabad India

ISBN: (纸本)9798350305449

In recent years, Urdu optical Character Recognition (OCR) systems have received considerable attention due to the increasing demand for automated recognition and analysis of text, which requires the development of robust OCR systems to convert printed and handwritten Urdu text into digital format. This article aims to provide a comprehensive overview of the most recent advances in OCR systems for Urdu. Analysing and synthesising 30 relevant research articles published between 2018 and 2023 to determine their contributions and future directions. Numerous studies have explored the use of deep neural networks, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory networks (LSTMs), to achieve high accuracy in character recognition by incorporating evolutionary algorithms, transfer learning, augmentation, and holistic unconstrained recognition systems. These models have demonstrated promising offline and online Urdu handwriting recognition results. The reviewed articles also shed light on the difficulties and limitations of existing Urdu OCR systems, such as the lack of standardised datasets, the dearth of annotated training data, and the need for robustness against noise and variations in handwriting styles. The literature discusses the development of more efficient algorithms, the investigation of multi-domain approaches, and the integration of deep learning techniques with other image processing techniques as future directions. The findings of this review will help researchers and practitioners in understanding the most recent techniques and challenges in Urdu OCR systems. © 2023 IEEE.

关键词： optical character recognition

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Efficient Low Light video Enhancement Based on Improved Retinex algorithms

Efficient Low Light Video Enhancement Based on Improved Reti...

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2023 IEEE International conference on Multimedia and Expo Workshops, ICMEW 2023

作者： Lee, Sung-Ling Yang, Shih-Hsuan National Taipei University of Technology Department of Computer Science and Information Engineering Taipei Taiwan

ISBN: (纸本)9798350313154

videos shot in low-light environments suffer from low contrast and high noise. In this paper, an improved zero-reference low-light enhancement technique for videos based on the Retinex model is presented. The proposed method improves the existing Retinex approaches in several aspects. First, the image features extracted by the VGG network are employed as a part of the input to the generator of the Retinex parameters for increasing temporal stability. Second, a deformable convolution kernel is used to enhance the spatial correlation. Third, the optical flow between frames is approximated as a combination of affine linear transformations for reducing complexity. Compared with the state-of-the-art low-light enhancement algorithms, the proposed method achieves more favorable and stable image qualities in PSNR and SSIM with short processing time. © 2023 IEEE.

关键词： Linear transformations

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