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

共 4293 条记录，以下是51-60 订阅

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Method for background replacement of certification photos

Method for background replacement of certification photos

引用

2024 International conference on Optics, Electronics, and Communication Engineering, OECE 2024

作者： Chen, Xu Zhang, Jihong Du, Yufei Sha, Zihuan Qiu, Rongfei Xu, Zezhong School of Computer Science and Information Engineering Changzhou Institute of Technology Jiangsu Changzhou213032 China

ISBN: (纸本)9781510685437

In order to overcome defects resulted from replacing the photo background color, an improved method is proposed for background replacement. The α-values in the alpha matte are transformed to enhance the details in the transition area. The new photo is composited by comprehensively considering the foreground portrait, new background, old background and the alpha matte. The experimental results show that the foreground portrait appears clearer and more complete, and the transition area between the foreground and background is more harmonious and more natural. © 2024 SPIE.

关键词： Color Opacity Computer science Engineering Image processing Image processing algorithms and systems Image processing software Image segmentation information science

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Employing Machine Learning Paradigms for Optimized Hard Disk Failure Prediction in Shipboard systems 4

Employing Machine Learning Paradigms for Optimized Hard Disk...

引用

4th International Computational Imaging conference, CITA 2024

作者： Ma, C. Li, F. Gao, D. Zhao, Y. Bao, T. Li, X. China Ship Research and Development Academy Beijing China State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9781510688834

This paper presents an optimized machine learning-based approach for hard disk failure prediction, specifically tailored for shipboard systems. In shipboard systems, unexpected hard disk failures can disrupt operations and lead to critical data loss;therefore, reliable failure prediction is essential. To address the impact of dataset imbalance on predictive performance, we employed the Synthetic Minority Over-sampling Technique (SMOTE) alongside a fault-backtracking method to transform the imbalanced dataset into a balanced one, thereby enhancing the algorithm's predictive accuracy. Four machine learning algorithms were utilized in this study: K-Nearest Neighbors (KNN), Logistic Regression (LR), Extreme Gradient Boosting (XGBoost), and Random Forest (RF). Experimental results demonstrated that the RF algorithm achieved an accuracy of 97.1%, outperforming the other algorithms across all evaluation metrics. The contribution of this work lies in providing a feasible solution for hard disk failure prediction in shipboard systems through effective data processing strategies and algorithm selection, ultimately enhancing shipboard safety and reliability. © 2025 SPIE.

关键词： Hard disk storage

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Algorithm for Changing the Size of a Multi-Element Aperture of a Two-dimensional Recursive-Separable Five-Stage Filter for Digital Image processing 25

Algorithm for Changing the Size of a Multi-Element Aperture ...

引用

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

作者： Kamenskiy, Andrey v. Kupriyanova, Kristina S. Podnebesnyy, Andrey v. Kuryachiy, Mikhail I. Borodina, Natalya Tatyana, Akaeva M. Dept. of Television and Control Tomsk State University of Control Systems and Radioelectronics Tomsk Russia

ISBN: (纸本)9798350389234

The paper presents a description of the developed algorithm for changing the size of a multi-element aperture of a recursive-separable five-stage filter for processing digital images generated by specialized optical systems. The developed algorithm has two features: it has the ability to change the size of a multi-element aperture during use;it makes it possible to use the recursive and separable properties. These capabilities make it possible to reduce the processing time of incoming data, which has a positive effect on the efficiency of the optical-electronic imaging system used. The paper presents a block diagram of a two-dimensional recursive-separable five-stage filter, with the help of which an algorithm was developed for changing the size of a multi-element aperture, and a study of the influence of the aperture size on the performance of the developed filter was carried out. As part of the performance evaluation, the developed algorithm was compared with the classical two-dimensional convolution algorithm. Developed algorithm was tested on three test images of different sizes and formats: 1300x700 Bitmap Picture, 1200x1200 Tagged Image File, 2900x1900 Joint Photographic Experts Group. During the processing of test images, the dimensions of the multi-element aperture of the developed filter changed. As the aperture size increases, the performance evaluation results also increase. This shows that speeding up the algorithm is an actual task. However, the developed algorithm takes less time than the classical two-dimensional convolution algorithm, from which it can be concluded that the developed solution is effective for both conventional images and images from optoelectronic systems. © 2024 IEEE.

关键词： digital filters digital image processing optical-electronic systems performance real time recursively separable algorithms

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Feed-forward Neural Network based Algorithm for Intelligent Positioning of Direction Finding Crossings 16

Feed-forward Neural Network based Algorithm for Intelligent ...

引用

16th International conference on Signal processing systems, ICSPS 2024

作者： Li, Pangzhe Hu, Dexiu Zhao, Chuang Information Engineering University Signal Processing Laboratory China

ISBN: (纸本)9781510689251

This paper proposes a feed-forward neural network(FNN) based algorithm for intelligent positioning of angle of arrival(AOA) to address the problems of complex computation, slow positioning speed and low positioning accuracy of traditional cross-location direction finding methods. The algorithm obtains the position of a known target from the available data, calculates its angle of arrival at the observatory, combines them into data pairs, and inputs them into a constructed neural network to obtain the corresponding model. The network can then locate unknown targets. It is verified that the algorithm has reliable localization accuracy and higher robustness than conventional algorithms. The proposed method also shows that the training of the neural network on the basis of a large amount of data can greatly reduce the operation time and achieve real-time target localization. © 2025 SPIE.

关键词： Neural network models

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Recognition and Analysis of Glass Subsurface Defects by Integrating Machine vision and Image processing Technology 5

Recognition and Analysis of Glass Subsurface Defects by Inte...

引用

5th International conference on Computers, information processing and Advanced Education, CIPAE 2024

作者： Lin, Chen Ling, Xiong Luo, Guangming Wuhan University of Science and Technology Wuhan China Changli Glass Honghu Co. Ltd Wuhan China

ISBN: (纸本)9798331527662

Machine vision and computer image processing technologies are widely used in the metallurgical industry, especially in recognizing and analyzing defects in glass. High surfaces of planer surface and quality in the glass and metal manufacturing sector primarily require automated and performance visual detection, and inspection systems and algorithms are constantly improving. This article, therefore, seeks to comprehensively recognize and analyze glass subsurface defects through the integration of image processing technologies and machine vision. According to the algorithm's properties and the image features typified in the process, the defects of identified glass components are primarily classified based on determining the cause and the optical features of characteristics exhibited. Given the nature of varied and detected effects determined mainly by the classifiers, an improved accuracy level was notable, and a reduction of the computational complexity was evident following the use of machine vision and image processing technologies. © 2024 IEEE.

关键词： Machine vision

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Research on the processing algorithm for solar cell characterization data 2

Research on the processing algorithm for solar cell characte...

引用

2nd International conference on Electronic information Engineering and Computer Communication, EIECC 2022

作者： Gui, Ruoxia Cheng, Jin Li, Junming Zhang, Chunqian Qin, Lei Research Center for Sensor Technology Beijing Key Laboratory for Sensor School of Applied Sciences Beijing Information Science and Technology University Jianxiangqiao Campus Beijing100101 China Beijing Key Laboratory for Optoelectronic Measurement Technology Beijing Information Science & Technology University Beijing100192 China

ISBN: (纸本)9781510663121

The research of solar cells has gone through three generations, silicon solar cells, thin film solar cells and perovskite solar cells. There are a variety of characterization methods used to analyze the factors that affect the performance of solar cells. Thus far, there are some deficiencies in the research of algorithms of the characterization methods themselves. Three types of data: current density-voltage (J-v) curves, X-ray diffraction (XRD) spectrum and absorption spectrum are the most essential characterization methods. Here, the processing algorithms of these three kinds of characterization data are studied, intend to help researchers to solve the practical problems more efficiently, and improve the accuracy of experimental results. In this paper, the process of processing algorithm are summarized in the way of flow chart, and combined with the example to show in turn. © 2023 SPIE.

关键词： Silicon solar cells

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A method for integrating operation and maintenance data of power information systems based on artificial intelligence technology 3

A method for integrating operation and maintenance data of p...

引用

3rd International conference on Machine vision, Automatic Identification, and Detection, MvAID 2024

作者： Liu, Peng Wang, Dazhong Zhang, Yuxi Ren, Yusong Ren, Jiandong China Electric Power Research Institute Beijing100192 China

ISBN: (纸本)9781510681880

The conventional method of integrating operation and maintenance data for power information systems is often time-consuming and suffers from limited data coverage. Consequently, this paper proposes a new method for integrating such data using artificial intelligence technologies. Initially, we set a unified standard and classification guideline for the integration process of operation and maintenance data in power information systems, identifying data types based on their interrelationships. We then organize and process the operation and maintenance data, removing any inconsistencies and redundancies to minimize the impact of irrelevant data and enhance integration efficiency. Furthermore, we implement a standardized coding system to verify and encode the organized data, ensuring it corresponds accurately with the actual datasets. By leveraging deep learning algorithms on offline data, this approach not only minimizes system resource utilization but also increases the extent of effective data coverage. Experimental outcomes indicate that this integration approach not only accelerates the process but also achieves greater data inclusivity compared to traditional methods, thus offering significant practical value. © 2024 SPIE.

关键词： Data integration information fusion Artificial intelligence Deep learning Classification systems information operations Data processing Evolutionary algorithms Power grids Standards development

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List and Certificate Complexities in Replicable Learning 37

List and Certificate Complexities in Replicable Learning

引用

37th conference on Neural information processing systems (NeurIPS)

作者： Dixon, Peter Pavan, A. vander Woude, Jason vinodchandran, N. v. Iowa State Univ Ames IA 50011 USA Univ Nebraska Lincoln Lincoln NE USA

ISBN: (纸本)9781713899921

We investigate replicable learning algorithms. Informally a learning algorithm is replicable if the algorithm outputs the same canonical hypothesis over multiple runs with high probability, even when different runs observe a different set of samples from the unknown data distribution. In general, such a strong notion of replicability is not achievable. Thus we consider two feasible notions of replicability called list replicability and certificate replicability. Intuitively, these notions capture the degree of (non) replicability. The goal is to design learning algorithms with optimal list and certificate complexities while minimizing the sample complexity. Our contributions are the following. - We first study the learning task of estimating the biases of d coins, up to an additive error of epsilon, by observing samples. For this task, we design a (d + 1)-list replicable algorithm. To complement this result, we establish that the list complexity is optimal, i.e there are no learning algorithms with a list size smaller than d + 1 for this task. We also design learning algorithms with certificate complexity (O) over tilde (log d). The sample complexity of both these algorithms is (O) over tilde (d(2)/epsilon(2)) where e is the approximation error parameter (for a constant error probability). - In the PAC model, we show that any hypothesis class that is learnable with d-nonadaptive statistical queries can be learned via a (d + 1)-list replicable algorithm and also via a (O) over tilde (log d)-certificate replicable algorithm. The sample complexity of both these algorithms is (O) over tilde (d(2)/nu(2)) where. is the approximation error of the statistical query. We also show that for the concept class d-THRESHOLD, the list complexity is exactly d + 1 with respect to the uniform distribution. To establish our upper bound results we use rounding schemes induced by geometric partitions with certain properties. We use Sperner/KKM Lemma to establish the lower bound results.

关键词： Learning algorithms

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Multichannel optical Fibers for the Network F5G

Multichannel Optical Fibers for the Network F5G

引用

2024 systems of Signals Generating and processing in the Field of on Board Communications, SOSG 2024

作者： Korshunov, v.N. Likhachev, N.I. Ovchinnikova, I.A. Shishova, N.A. Semenov, P.A. Moscow Technical University of Communications and Informatics Moscow Russia JSC VNIIKP Moscow Russia

ISBN: (纸本)9798350383614

The aspects of the application of multichannel optical fibers in cables and transmission systems of fixed networks F5G are investigated. The loop of optical cable quality and quality management with ensuring the required efficiency are considered. Analytical expressions are given to evaluate the throughput and efficiency of multichannel fibers, and numerical values of efficiency are given. The random process of fiber irregularity with the behavior of directional and resultant modes is described, experimental data are presented. The solution of the problem of optimizing the linear path of the transmission system has been described, the maximum length of the path without intermediate signal regeneration has been calculated. ©2024 IEEE.

关键词： optical fibers

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Scientific and Methodological Support for the Interoperability of Intelligent Transport systems

Scientific and Methodological Support for the Interoperabili...

引用

2024 systems of Signals Generating and processing in the Field of on Board Communications, SOSG 2024

作者： Drogovoz, v.A. Pashkov, A.A. Federal Research Center "Computer Science and Control" the Russian Academy of Sciences Moscow Russia Moscow Technical University of Communications and Informatics Moscow Russia

ISBN: (纸本)9798350383614

The main trends in the development of intelligent transport systems are considered. It is shown that the relevance of the problem of interoperability is increasing in the context of digital transformation of the transport industry. One approach to ensuring interoperability is open systems technology and functional standardization. Methodological approaches to localizing interoperability barriers for further optimization are considered and problems are formulated that can be solved using fuzzy logic calculation algorithms. ©2024 IEEE.

关键词： Standardization

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