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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems XI"

共 16444 条记录，以下是1661-1670 订阅

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A Genetic Algorithm Based Method for Detecting Intermediate Accounts in Money Laundering Through Analysis of Temporal Graphs

A Genetic Algorithm Based Method for Detecting Intermediate ...

引用

6th International conference on Intelligent Computing and Signal processing (ICSP)

作者： Peng Liu Tong Chen College of Computer Science and Technology Xi'an University of Science and Technology Xi'an Shannxi China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

The detection of intermediate accounts in money laundering plays a crucial role in the process of anti-money laundering. Criminals are constantly developing new techniques to avoid detection, such as mixing money laundering transactions with a few normal transactions to disguise suspicious transfers. Existing methods do not take this into account and assume that all funds passing through intermediate accounts are associated with illegal transactions. This paper proposes a genetic algorithm based method for detecting intermediate accounts disguised in participation of a few nomal transations. Transations are expressed as a temporal graph. Each edge describes the time and amount of one transation. A suspicious intermediate account meets the condition that an in-edge subset and an out-edge subset are matched. Two edge subsets are matched means that they have similar total amounts and approximate time span. The genetic algorithm is used to search mathched in-edge and out-edge subsets. Experimental results demonstrate that the proposed method outperforms Decision Tree and Naive Bayes in terms of recall, precision, and F1_Score metrics in the identification of intermediate accounts involved in money laundering.

关键词： Measurement image edge detection Signal processing algorithms Transforms Signal processing Search problems Bayes methods Decision trees Optimization Genetic algorithms

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A Conversion Algorithm for ECG signals on a 2D array based on Digital Signal processing 11

A Conversion Algorithm for ECG signals on a 2D array based o...

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11th International conference on Communications, Circuits and systems (ICCCAS)

作者： Cesar Cabanillas, Julio Kemper, Guillermo del Carpio, Christian Univ Peruana Ciencias Aplicadas Fac Engn Sch Elect Engn Lima Peru

ISBN: (数字)9781665469890

ISBN: (纸本)9781665469890

This work proposes a computational algorithm to convert digital files containing electrocardiogram (ECG) information into 1D signals. Many medical databases have in storage files containing ECG information that is not easy to process for computational algorithms. Digitization by the proposed method makes it possible to modernize the databases of many health centers in order to perform post-processing of the signals obtained. This method is based on applying digital signal processing techniques to images obtained from a PDF file produced by an electrocardiograph. The proposed algorithm takes into consideration the thickness of the printed signal in the PDF image so that it does not introduce distortion in the final 1D signal. Due to the distribution of the ECG signals on the PDF files the algorithm identifies and segments the signals on 2 dimensions. The results show that the proposed method can correctly reproduce the information of the ECG waves captured in the PDF file regardless of the elements outside the ECG signal such as the background grid or the different information indicators, whether they are labels or references of the ECG signals. The algorithm has an accuracy of 95% based on the statistical analysis performed for all samples.

关键词： Digital Signal processing ECG signals Conversion Printed Signal Digitization 2D array

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Automatic Recognition of Non-standard Number Plates using YOLOv8 18

Automatic Recognition of Non-standard Number Plates using YO...

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18th INDIAcom;11th International conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Tupsounder, Asaavi Patwari, Renuka Ambati, Roja Chavarkar, Arya Shirsat, Kavita Vidyalankar Institute of Technology Dept. of Computer Engineering Mumbai India

ISBN: (纸本)9789380544519

A critical feature of vehicle movement applications is the detection and identification of a vehicle's License Plate (LP). Despite technological and algorithm developments, differences in LP properties by nation, such as number system, colors, character language, fonts, and size, necessitate more study to enhance detection and recognition. Despite substantial study, many systems function in well-defined contexts, necessitating the use of expensive equipment to capture photos from slow-moving vehicles or generate high-quality shots. This study describes a deep learning-based automated approach for LP detection and recognition, which is further separated into detection and character recognition. Yolov8 (You Only Look Once Version-8) was utilized for automatic pixel separation and gradient computation, making complicated model training easier. Using deep learning, Easy OCR (Optical Character Recognition) was utilized to retrieve text from number plates. Easy OCR (Optical Character Recognition) was utilized to extract text from license plates, with deep learning algorithms employed to effectively read text in difficult settings. For image and video processing, OpenCV (Open-Source Computer Vision Library) was employed. The project titled 'Automatic Number Plate Using YOLOv8 Model' leverages the advanced capabilities of the YOLOv8 model to develop a robust system for automated number plate recognition, serving as the core component for real-time object detection and number plate localization within images and video streams. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： ANPR (Automatic Number Plate Recognition) Deep learning image Recognition Non-Standard OpenCV YOLOv8

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Comparing the Effectiveness and Performance of image processing algorithms in Face Recognition

Comparing the Effectiveness and Performance of Image Process...

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International Carpathian Control conference (ICCC)

作者： Hussam M. Rostum József Vásárhelyi Institute of Automation and Info-Communication University of Miskolc Miskolc Hungary

ISBN: (数字)9798350350708

ISBN: (纸本)9798350350715

Many institutions have recently embraced biometric security solutions, utilizing biological measurements to safeguard against fraudulent activities, theft, and various security threats. Face recognition technology holds a pivotal role within the realm of bio-metric security systems, serving purposes such as authentication, monitoring, individual identification, and identity verification. This article aims to delve into the examination of facial recognition systems grounded in deep learning. This focus arises due to the intricate nature of the process and the existence of numerous hurdles and variables that impact algorithm performance. The objective here is to illuminate the foremost challenges that real-world systems encounter, often overlooked in previous research. Additionally,under these challenges, the article will conduct a comparative analysis of the performance of prominent facial recognition algorithms, namely VGGFace, FaceNet, and ArcFace. This academic approach will allow to make informed choices when selecting the most suitable algorithms for specific applications.

关键词： Deep learning Employee welfare Databases Face recognition image processing Lighting Biology

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Research on Application of Fractional Calculus and Fish School Algorithm in Statistics under the Background of "Internet+"

Research on Application of Fractional Calculus and Fish Scho...

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6th International conference on Intelligent Computing and Control systems, ICICCS 2022

作者： Guo, Qianru Shaanxi Business College School of Accounting and Finance Shaanxi Xi'an 710019 China

ISBN: (纸本)9781665410359

On the basis of expounding the related theory of fractional calculus, this article summarizes the engineering application of fractional calculus, analyzes the realization theory of relevant fractional calculus in statistics, and finally elaborates the fractional calculus in statistics. The practical application of integration provides a certain reference for the signal processing application of fractional calculus. Finally, in order to verify the effect of the above improved normal distribution enhancement method, a simulation experiment was carried out on the Matlab platform, and the image quality parameters obtained from the experiment were calculated. The results showed that the effect was increased by 6.7%. © 2022 IEEE.

关键词： Normal distribution

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Hyperspectral Band Selection Based on Classification Reward Adjustment

Hyperspectral Band Selection Based on Classification Reward ...

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IEEE Internatonal conference on Mobile Adhoc and Sensor systems (MASS)

作者： Jing Hu Jiawei Liang Yunfei Ju Minghua Zhao Shaanxi Key Laboratory for Network Computing and Security Technology School of Computer Science and Engineering Xi'an University of Technology Xi'an China

ISBN: (数字)9798350363999

ISBN: (纸本)9798350364002

Hyperspectral image band selection is a crucial link in image processing. It is necessary to screen out bands with rich information and low correlation, to achieve data dimensionality reduction and retain key information, thereby improving image processing efficiency. Aiming at the differences in reflectance characteristics of targets in different regions in hyperspectral images and the strong correlation between bands, this paper proposes a gradient-guided spatial-spectral weighted hyperspectral band selection method. Firstly, gradient information is introduced to enhance the edge texture features of different targets. Then, the entropy rate superpixel segmentation algorithm is used to segment the first principal component of the image and divide multiple uniform regions. Secondly, to more comprehensively capture the global relationship between all bands in the image, a multi-graph complementary strategy is proposed to construct a regional similarity graph, aiming to maximize the mutual contribution between superpixels with spatial-spectral similarity. Finally, a unified clustering graph is generated by spectral clustering. After normalized cutting, the band with the least noise information in each sub-cube is selected to form a new band subset. The effectiveness of the proposed method is verified by classification experimental results and data analysis.

关键词： Training Reflectivity image segmentation Correlation Noise Memory modules Predictive models Smart systems Spatiotemporal phenomena Hyperspectral imaging

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image Generation and Feedback Based on Deep Learning in Visual Communication Design

Image Generation and Feedback Based on Deep Learning in Visu...

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Evolutionary algorithms and Soft Computing Techniques (EASCT), International conference on

作者： Ganlin Cheng Xi'an Academy of Fine Arts Xi'an China

The feedback process plays an important role in visual communication design and has a profound impact on the effect of visual information transmission. This paper takes image generation as the main line, and focuses on the analysis of feedback behavior in two ways: real-time interaction and data synchronization acquisition. The study found that with the help of deep learning methods, it can effectively promote the expression of the relationship between the outputter and the viewpoint and the position in the graphical memory task, and improve the ability to map attributes such as images. This paper also conducts a functional test analysis of the platform, and the test results show that the processing time of the platform is between 2 seconds and 4 seconds. The flexible control of the time required for the feedback process is realized in the form of pictures, which further improves the effect of visual communication design. By learning a large amount of image data, these models can automatically identify and repair defects in images, such as blurring, noise, and missing parts. Research has found that deep learning based image restoration and enhancement techniques have made significant improvements in restoring image quality.

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A Two-Stage Multispectral Demosaicking Method Using Neville Filters and Directional Interpolation

A Two-Stage Multispectral Demosaicking Method Using Neville ...

引用

Signal, Information and Data processing (ICSIDP), IEEE International conference on

作者： Wenzhuo Yang Yakun Liu Yan Shi Wei Li Ran Tao School of Information and Electronics Beijing Institute of Technology Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Snapshot multispectral imaging systems typically capture multispectral images in a single shot by covering the sensor with a multispectral filter array (MSFA). A demosaicking algorithm is generally required for such systems to reconstruct the full-resolution multispectral images. A two-stage demosaicking method is proposed in this paper. In the first stage, the image is progressively interpolated by Neville filters. In the second stage, the directional interpolation with a novel weighting function is performed to enhance the quality of the pre-interpolated image. Experimental results demonstrate that the proposed approach achieves superior performance in both subjective and objective assessments.

关键词： Interpolation Multispectral imaging Array signal processing Filtering algorithms Information filters Data processing image reconstruction Sensor arrays

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Removal of Impulse Noise from Colour image Using Different Variations of Non-Linear Filters

Removal of Impulse Noise from Colour Image Using Different V...

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Engineering and Technology (PICET), Parul International conference on

作者： Aakanksha Jain Harshal Arolkar GLS University Ahmedabad India

ISBN: (数字)9798350369748

ISBN: (纸本)9798350369755

Digital images are affected by a variety of noise and one well-known type is impulsive noise. In order to reduce or eliminate noise, many image-denoising algorithms have been created, with varying benefits and limitations. To deal with impulsive and spurious noise in colour images, this study does a thorough examination with an emphasis on the median filter and its various variants. By means of thorough experimentation, the researchers examine the relative performance of different denoising algorithms using Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) as standards. The results of the study demonstrate the usefulness of the Vector Median filter, especially in situations with high-density impulsive noise. The Vector Median filter is particularly effective for real-time image processing applications since it performs better and requires less processing time. Furthermore, the Modified Median filter, with its high PSNR and low MSE values, shows potential as a low-density noise solution. This study offers insightful information about image eliminating techniques aimed at reducing impulsive noise in colour images. The study advances the field of image processing by utilising creative methodologies and performance measurements. This has significance for other sectors that depend on accurate image analysis. The study also sets the basis for next investigations focused on improving and expanding the range of denoising algorithms to handle a greater variety of noise kinds and intensities.

关键词： PSNR image color analysis Noise reduction Mean square error methods Filtering algorithms Information filters Vectors Real-time systems Colored noise Standards

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Research on image processing algorithms Based on Variational and Deep Learning

Research on Image Processing Algorithms Based on Variational...

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Mechatronics, IoT and Industrial Informatics (ICMIII), International conference on

作者： xiaoxu Zhang Heilongjiang Polytechnic Harbin China

ISBN: (数字)9798350386639

ISBN: (纸本)9798350386646

China has seen an unheard-of surge in interest in deep-learning methods for image restoration in recent years. Most of these strategies draw inspiration from the established variational technique and related optimization methods for the picture reconstruction inverse issue. While using learnable components to create organized deep neural networks and using copious amounts of observation data to train the networks for the particular reconstruction objectives, these techniques resemble the iterative strategies of ordinary optimization algorithms. In many cases, they have proven to have far better empirical performance than the conventional approaches, and they also demand a lot lower computing cost. For various common networks in this subject, this research offers the specifics of the derivations, the network topologies, and the training protocol. The research therefore focuses on image processing algorithms based on variational and deep learning models.

关键词： Training Deep learning Sensitivity Protocols Optimization methods Visual systems Retina

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