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

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Using image processing and Optical Character Recognition to Recognise ID cards in the Online Process of Onboarding

Using Image Processing and Optical Character Recognition to ...

引用

2022 International conference on Smart Information systems and Technologies, SIST 2022

作者： Gulnara, Bektemyssova Yerassyl, Akhmer International Information Technology University Almaty Kazakhstan

ISBN: (数字)9781665467902

ISBN: (纸本)9781665467902

A broad range of computer vision studies have been conducted on the recognition of identity documents using mobile devices. A portfolio of techniques and algorithms for solving problems like face recognition, document detection and correction, text field recognition, and so on has been developed, and the lack of data sets has become a critical challenge. The electronic ID card has been commonly used to verify or recognize an individual since its discovery in 2011. Take note of several issues, such as high requirements for detecting the id-card field and challenges recognizing the data in the id-card. In this research, we realized an approach for identifying electronic ID cards using image detection and Optical Character Recognition (OCR). This paper provides a short outline of how banking institutions and other fintech companies utilize highly developed OCR tools to automate their processes, enhancing not just service quality, as well as the precision, speed, and protection of their transaction data. As an outcome of our image processing and OCR techniques, we can achieve 99 percent ID detection. This research was based on the interface of a mobile application, such as those owned by one of Kazakhstan's banks. © 2022 IEEE.

关键词： Optical character recognition

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SWT-UNet: Medical image Segmentation Based on Multi-modality UNet with Sliding Window Transformer Block

SWT-UNet: Medical Image Segmentation Based on Multi-modality...

引用

2023 IEEE International conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Zhang, Yangqianhui Han, Dong Gang, Xiaoming Ma, Jiajun Yuan, Xu Zhejiang University School of Mechanical Engineering Hangzhou China Zhejiang University State Key Laboratory of Fluid Power and Mechatronic Systems Hangzhou China Anshan Municipal Central Hospital Anshan China Shenhua Hollysys Information Technology Co. Ltd Beijing China Dalian University of Technology School of Software Technology Dalian China

ISBN: (纸本)9798350337488

Medical images are information carriers that visually reflect and record the anatomical structure of the human body, and play an important role in clinical diagnosis, teaching and research, etc. Modern medicine has become increasingly inseparable from the intelligent processing of medical images. In recent years, there have been more and more attempts to apply deep learning theory to medical image segmentation tasks, and it is imperative to explore a simple and efficient deep learning algorithm for medical image segmentation. In this paper, we conduct research on multi-modal medical image segmentation algorithms with a hybrid architecture of Convolutional Neural Networks and Vision Transformer. This paper proposes a multi-modal medical image segmentation model SWT-UNet based on the CNN-ViT hybrid framework. The self-attention mechanism and sliding window design of the visual Transformer are used to capture the global feature association and break the limitation of the receptive field caused by the inductive bias of the convolution operation. At the same time, a widened self-attentive vector is used to streamline the number of modules and compress the model size, so as to fit the characteristics of a small amount of medical data, which makes the model easy to be overfitted. Experiments on two multi-modal medical image datasets validate that the algorithm can achieve efficient medical image segmentation at a lightweight scale. © 2023 IEEE.

关键词： attention mechanism medical image segmentation multi-modality Vision Transformer

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ADHHI airborne hyperspectral imager: camera structure and geometric correction 28

ADHHI airborne hyperspectral imager: camera structure and ge...

引用

conference on image and Signal processing for Remote Sensing XXviiI

作者： Dong, Jieke Duan, Yansong Zhou, Qi Zhao, Xinbo Wuhan Univ Sch Remote Sensing & Informat Engn Wuhan 430079 Peoples R China

ISBN: (纸本)9781510655386;9781510655379

For decades, the design of remote sensors has to make trade-offs among many characteristics such as the field of view (FOV), spatial resolution, spectral resolution, radiometric resolution, and the number of bands. It's inevitable to weaken some characteristics to enhance others. Moreover, these problems lead to using multi-sources of remote sensing data in practical projects where a single sensor can't meet the relevant requirements. The Airborne Dual-mode High-resolution Hyperspectral imager (ADHHI) provides a new solution to the above limitations by the technology of multi-camera stitching. In this way, many excellent but conflicting characteristics can be separated into different imaging sub-systems, and are combined together during data processing. Supported by related processing algorithms and software, ADHHI embeds many excellent characteristics into one system, such as high spatial resolution, high spectral resolution, and high radiometric resolution. Firstly, this paper picks some common imaging sensors to illustrate the problem of conflicting characteristics. Secondly, we introduce the camera structure and sensor parameters of ADHHI. Then, we sketch out the data processing workflow and elaborate on relevant principles and results of the whole geometric correction, such as homospectral stitching and hetero-spectral registration. Finally, this airborne hyperspectral imager's advantages and application prospects are concluded.

关键词： geometric correction image stitching hyperspectral imager airborne pushbroom

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Survey of Approaches to Non-Realistic Neural Style Transfer 31

Survey of Approaches to Non-Realistic Neural Style Transfer

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31st conference of Open Innovations Association FRUCT, FRUCT 2022

作者： Varlamova, Arina Kitov, Victor Lomonosov Moscow State University Moscow Russia

ISBN: (纸本)9789526924472

Despite researchers interest toward style transfer problem, there is still no foremost method available. Difficulties in problem formalization make a comparison of methods especially complicated. This paper covers twelve widely used algorithms in order to provide their comprehensive description and advantages one over another. © 2022 FRUCT Oy.

关键词： Technological innovation image processing Real-time systems Convolutional neural networks

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Exploration of Motion Increase Rate Based on Infrared Feature Capture and CFD Numerical Simulation

Exploration of Motion Increase Rate Based on Infrared Featur...

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Electronics, Energy systems and Power Engineering (EESPE), IEEE International conference on

作者： Minghan Wang Beijing University of Technology Beijing China

ISBN: (数字)9798350389579

ISBN: (纸本)9798350389586

The purpose of this study is to explore the motion incremental speed technology based on infrared feature capture and CFD numerical simulation, through the sensor, image processing and analysis algorithms, etc. On the basis of exploring the target's motion characteristics, combined with the Chancellor's theory of ballistic trajectory, and real-time capture of the target's thermal feature information is to achieve accurate target tracking and motion trajectory adjustment. Firstly, this paper adopts the image processing and analysis algorithm, and uses the normal distribution model to process the infrared data, so as to construct the target motion model. Secondly, CFD numerical simulation is used to analyse mechanisms such as motion boost guidance in order to provide more accurate target tracking and trajectory correction schemes. Finally, the motion region of the updraft is predicted by spherical averaging of the fluctuation equation. The results show that the infrared feature capture technique is able to maintain efficient motion track correction and motion speed-up capability based on real-time data processing in dynamic environments.

关键词： Target tracking Accuracy image processing Gaussian distribution Numerical simulation Mathematical models Real-time systems Data models Numerical models Trajectory

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Pneumonia Classification using deep learning: a comparative study

Pneumonia Classification using deep learning: a comparative ...

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International conference on image and Signal processing and their Applications (ISPA)

作者： Mohamed Lakhdar Tiar Nadjiba Terki Juan Jose Dominguez-Jimenez IL3CUB Laboratory University of Mohamed Khider Biskra Algeria Electrical Engineering Department University of Mohamed Khider Biskra Algeria Dept. Computer Languages and Systems University of Cadiz Escuela Superior de Ingenieria Cadiz Spain

ISBN: (数字)9798350309249

ISBN: (纸本)9798350309256

Pneumonia is an infectious disease of the lungs, caused by viruses, bacteria or fungi. Pneumonia is distinguished by acute inflammation of the lung tissue, causing the consolidation of the terminal bronchioles and alveoli. According to the WHO (the World Health Organization), this disease causes about 4 million deaths. Among the methods of diagnosing pneumonia uses a chest X-ray. This is widely used to visualize pulmonary abnormalities. This work aims at the detection and characterization of pneumonia by the development of computer-assisted diagnosis systems (DAOC). We use deep learning algorithms and chest X-ray images from a pneumonia database to examine the classification of pneumonia. To improve the accuracy, we compare several deep learning models. This research contributes to meeting the growing demand for medical personnel by addressing the global incidence of chest disorders.

关键词： Deep learning Visualization Pneumonia Lung Signal processing algorithms Medical services Signal processing

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Wirelessly Controlled Plant Health Monitoring and Medicate System Based on IoT Technology 1

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1st International conference on Advanced Network Technologies and Intelligent Computing (ANTIC)

作者： Ayalew, Lijaddis Getnet Mattihalli, Channamallikarjuna Asmare, Fanuel Melak Bahir Dar Univ Fac Elect & Comp Engn Bahir Dar Inst Technol Bahir Dar Ethiopia

ISBN: (数字)9783030960407

ISBN: (纸本)9783030960407;9783030960391

The availability of good quality fruits and vegetables is paramount in preventing starvation and minimizing outbreaks of diseases which leads to improving quality of life. One of the major obstacles of the mentioned availability is plant leaf disease. Although manpower plays a vital role in detecting such problems it is time-intensive, expensive, and very inefficient. Thus, developing a mechanism to vigorously monitor leaf's health and detect diseases of plant leaves at early stages is mandatory so that one can produce plenty. In this contribution, a system that detects leaf disease is developed using image processing algorithms, the k-nearest neighbor (KNN), support vector machine (SVM), and multilayer perception (MLP) machine learning algorithms are compared based on plant disease detection and classification systems performances. We also developed a prototype of simple-to-install technology that can recognize leaf diseases and allow medicine flow based on the results. This paper presents a smart plant health monitoring system that takes into account humidity, temperature, and soil contents.

关键词： image processing IoT KNN MLP SVM

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Experimental Results of Local Backprojection for Monostatic THz SAR Imaging

Experimental Results of Local Backprojection for Monostatic ...

引用

2025 International conference on Mobile and Miniaturized Terahertz systems, ICMMTS 2025

作者： Ivanenko, Yevhen Batra, Aman Vu, Viet Thuy Pettersson, Mats I. Kaiser, Thomas Blekinge Institute of Technology Karlskrona371 79 Sweden University of Duisburg-Essen Duisburg470 57 Germany

ISBN: (纸本)9798350365832

The use of THz frequencies has enabled the opportunity to perform synthetic-aperture radar (SAR) imaging at the sub-mm level. It is of great interest for applications where high-resolution remote sensing in short range is required. However, with the increase of the operating frequencies from microwave to THz, the SAR image formation algorithms work with a larger amount of data and become more sensitive to phase errors that can be caused by insufficient signal sampling rate or physical factors that cause platform deviations. This motivates the use of fast image formation capable to handle phase errors. In this paper, we present the experimental results on the performance of the local backprojection (LBP) algorithm for processing THz SAR signals. The LBP algorithm has been tested with the real data in the frequency range 0.325-0.5 THz. The results demonstrate the efficiency of the LBP algorithm for the SAR scene reconstruction and highlight the necessity of the use of two times higher signal upsampling to achieve reconstruction accuracy similar to the global backprojection algorithm. © 2025 IEEE.

关键词： image sampling

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A Novel Artistic image Compression Algorithm Based on Multi-Scale Adaptive Discrete Wavelet Transform

A Novel Artistic Image Compression Algorithm Based on Multi-...

引用

Multi-Agent systems for Collaborative Intelligence (ICMSCI), International conference on

作者： Yijun Li China Academy of Art Yuhang District Hangzhou Zhejiang China

ISBN: (数字)9798331509828

ISBN: (纸本)9798331509835

How to compress information is a challenge in the digital age, and the image compression has a wide range of application scenarios. In order to solve the challenges of low compression efficiency and high loss rate of the traditional algorithms, this study proposes a compression algorithm based on multi-scale adaptive discrete wavelet transform. The core of the proposed algorithm is to make reasonable use of the multiresolution analysis characteristics of discrete wavelet transform. Based on the feature extraction, the image information is decomposed into high-frequency and low-frequency parts. This operation can stably and effectively implement frequency domain threshold processing and reduce redundant data. The proposed algorithm optimizes the encoding efficiency of image features to the greatest extent by introducing block difference features and designing a new iterative function system. In view of the high redundancy and high complexity of the artistic images, the traditional wavelet analysis is improved and optimized, and a multi-scale adaptive model is introduced. In the experiment, the test used multiple sets of artistic image test sets and compared them with mainstream algorithms (JPEG, VAE, etc.). In PSNR analysis, the proposed algorithm achieves better performance.

关键词： image coding Wavelet transforms Transforms Discrete wavelet transforms Feature extraction Wavelet analysis Wavelet domain Compression algorithms Frequency-domain analysis Collaborative intelligence

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Segmentation of Electrical Discharge Processes Based on the image Analysis of Plasma-Electrolyte Oxidation 19

Segmentation of Electrical Discharge Processes Based on the ...

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conference on Electro-Optical and Infrared systems - Technology and Applications XIX

作者： Zhukov, S. Voronin, V. Semenishchev, E. Chudinov, D. Zhukova, O. Moscow State Univ Technol STANKIN Ctr Cognit Technol & Machine Vis Moscow Russia

ISBN: (纸本)9781510655461

In the process of plasma-electrolytic synthesis, a new physical surface is synthesized, consisting of a metal oxide layer of a modified surface and the synthesis of elements of a set of electrolyte plasma, the nodal sources of the components of which are the components of the electrodes (electrolyte and metal surface). In this regard, the classification of plasma electro-discharge processes based on analyzing optical and electrical sensor data using machine learning methods is an actual task. It can be used for intelligent control algorithms of the sensor layers operations and conduct analytical and quantitative studies of the properties of nodal substances. The paper presents the experimental analysis of video and electrical parameters of the oxygen process, automated processing of the basic features of images of plasma-electrolyte discharges, and a segmentation approach of the electric-discharge machining. This approach can help create microsensor elements and materials and systems for intelligent modeling and launching of electrochemical methods for creating an electrolyte plasma and directed synthesis of substances. To test the performance of the proposed algorithm, the database STANKIN is used.

关键词： segmentation image processing electrical discharge plasma-electrolyte oxidation

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