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

共 15614 条记录，以下是4761-4770 订阅

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Semantic processing of Radar Spectral Information for Air Object Recognition

Semantic Processing of Radar Spectral Information for Air Ob...

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International Scientific-Practical conference Problems of Infocommunications Science and Technology

作者： Svitlana Solonska Volodymyr Zhyrnov Oleksiy Holovin Kharkiv National University of Radio Electronics Kharkiv Ukraine Central Research Institute of Armaments and Military Equipment of the Armed Forces of Ukraine Kiev Ukraine

ISBN: (数字)9781728141848

ISBN: (纸本)9781728141855

The results of the study of semantic processing of spectral information in the intelligent radar systems are presented. A method for formalizing the processes of perception and transformation of spectral images based on algebra of finite predicates is developed. A model for semantic processing of spectral image for surveillance radars has been developed and implemented. To analyze the features of clutter spectra and air object signals authors investigate the decision making algorithms of a human-operator. Spectral pattern is described as a predicate on the set of spectral channels that exceed the certain threshold value. The predicates-signs are introduced to indentify spectral types. Instantaneous spectrum is corresponded to one type of spectrum by a combination of these predicates. A functional diagram for automatic identification of spectral types, based on these equations, is built. The algorithm for analyzing of the clutter spectrum and recognizing of the air objects, based on algebra of finite predicates, which is proposed in the paper, allows to define all signs and automatically recognize air objects in real time.

关键词： Radar imaging Semantics Reflection Algebra Atmospheric modeling Mathematical model

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Myocardial Scar Segmentation from Magnetic Resonance images Using Convolutional Neural Network

Myocardial Scar Segmentation from Magnetic Resonance Images ...

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conference on Medical Imaging - Computer-Aided Diagnosis

作者： Zabihollahy, Fatemeh White, James A. Ukwatta, Eranga Carleton Univ Dept Syst & Comp Engn Ottawa ON Canada Univ Calgary Libin Cardiovasc Inst Alberta Calgary AB Canada

ISBN: (数字)9781510616400

ISBN: (纸本)9781510616400

Accurate segmentation of the myocardial fibrosis or scar may provide important advancements for the prediction and management of malignant ventricular arrhythmias in patients with cardiovascular disease. In this paper, we propose a semi-automated method for segmentation of myocardial scar from late gadolinium enhancement magnetic resonance image (LGE-MRI) using a convolutional neural network (CNN). In contrast to image intensity-based methods, CNN based algorithms have the potential to improve the accuracy of scar segmentation through the creation of high-level features from a combination of convolutional, detection and pooling layers. Our developed algorithm was trained using 2,336,703 image patches extracted from 420 slices of five 3D LGE-MR datasets, then validated on 2,204,178 patches from a testing dataset of seven 3D LGE-MR images including 624 slices, all obtained from patients with chronic myocardial infarction. For evaluation of the algorithm, we compared the algorithm-generated segmentations to manual delineations by experts. Our CNN-based method reported an average Dice similarity coefficient (DSC), precision, and recall of 94.50 +/- 3.62%, 96.08 +/- 3.10%, and 93.96 +/- 3.75% as the accuracy of segmentation, respectively. As compared to several intensity threshold-based methods for scar segmentation, the results of our developed method have a greater agreement with manual expert segmentation.

关键词： image segmentation 3D image processing Convolutional neural networks image processing algorithms and systems Algorithm development Magnetic resonance imaging

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Analysis of reliability, survivability and telemetry data of on-board equipment of small satellites

Analysis of reliability, survivability and telemetry data of...

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International conference on CAD systems in Microelectronics (CADSM)

作者： Vadim Skobtsov Natalia Lapitskaja Dmitriy Kim Natalia Novoselova Roman Saksonov Eugene Nikolaenya Problems of Information Security Laboratory United Institute of Informatics Problems of NAS Belarus Minsk Belarus Dept. of Information Technology Software Belarusian State University of Informatics and Radioelectronics Minsk Belarus Bioinformatics Laboratory United Institute of Informatics Problems of NAS Belarus Minsk Belarus Geoinformation Systems Minsk Belarus

In paper we present the solution of relevant problems of estimation, analysis and forecasting the indicators of reliability and survivability of the onboard equipment of small satellites. The solution of the problem of intelligent data analysis of telemetry onboard equipment of small satellites in order to detect the states of its operation and do operability analysis. A set of software tools and techniques for the evaluation and analysis of reliability, survivability and telemetry of small satellites onboard equipment was developed. The developed software tools and techniques are based on the methods and algorithms of reliability theory, probability theory and mathematical statistics, Boolean algebra, machine learning and image processing. The suggested software tools set is implemented in desktop and web versions, and has a flexible service-oriented architecture.

关键词： Software reliability Software tools Telemetry Data analysis Estimation Probability

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algorithms of landmark robot navigation basing on monocular image processing 8

Algorithms of landmark robot navigation basing on monocular ...

引用

8th International conference Advanced Computer Information Technologies, ACIT 2018

作者： Koval, Vasyl Department of Information Computing Systems and Control Ternopil National Economic University 8 Chekhova str. Ternopil Ukraine

ISBN: (纸本)9789666544899

The application of mobile robots is very important in environments that are dangerous or inappropriate for human life. One of the problems arising for the mobile robot when targeting point within the indoor application during navigation is the provision of its localization. In this paper, the developments of the algorithms that provide and enable mobile robot to position itself within the indoor environment by using one video camera and a landmark template is presented. Copyright © 2018 for the individual papers by the papers'authors.

关键词： Mobile robots

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An Optimization Approach of Compressive Sensing Recovery Using Split Quadratic Bregman Iteration with l₀ Smoothed Norm 3

An Optimization Approach of Compressive Sensing Recovery Usi...

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3rd IEEE International conference on image processing, Applications and systems (IPAS)

作者： Yang, Guoan You, Yuning Lu, Zhengzhi Yang, Junjie Wang, Yuhao Xi An Jiao Tong Univ Sch Elect & Informat Engn 28 Xianning West Rd Xian 710049 Shaanxi Peoples R China

ISBN: (纸本)9781728102474

An optimization algorithm for image recovery is a core issue in the field of compressive sensing (CS). This paper deeply studied the CS reconstruction algorithm based on split Bregman iteration with l(1) norm, which enables the l(1) norm to approximate the original l(0) norm during the optimization process. Consequently, we proposed another novel algorithm improving the precision and the convergence speed based on split quadratic Bregman iteration (SQBI) with l(0) norm. Besides, we analyzed its convergence by proving two monotonically decreasing theorems. Inspired by previous researches, we applied smoothed l(0) norm for the optimization problem to replace the traditional to norm in CS. The improvement is made by using a Gaussian function to approximate the l(0) norm, transforming it into a convex optimization problem, and eventually achieved a convergent solution by the steepest descent method. The experimental results show that under the same conditions, compared with other state-of-the-art algorithms, the reconstruction accuracy of the CS reconstruction algorithm based on the SQBI with smoothed l(0) norm is improved significantly, and its convergence rate is also accelerated as well.

关键词： Compressive sensing sparse representation image recovery split qradratic Bregman iteration convex optimization

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Fusion Research of visible and Infrared images Based on IHS Transform and Regional Variance Wavelet Transform 10

Fusion Research of Visible and Infrared Images Based on IHS ...

引用

10th International conference on Intelligent Human-Machine systems and Cybernetics, IHMSC 2018

作者： Zeng, Xiangjin Tian, Jinwen School of Computer Science and Engineering Wuhan Institute of Technology Wuhan China Automation College Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781538658369

Aiming at the problem of low contrast between target and background in fusion of infrared and visible images, a fusion method of infrared and visible images based on IHS transform and wavelet region transformation is proposed. The first of the visible light IHS transform the luminance component of infrared image gray processing, then the luminance component of visible light and infrared image of three level wavelet transform to obtain high frequency component and low frequency component respectively, the low frequency sub-band coefficients fusion rules comparing the area difference, and then calculate the weighted wavelet coefficients;in the high frequency sub-band coefficients using regional variance adaptive fusion rules. The experimental results show that compared with other algorithms, the fusion image obtained by this method enhances the contrast between the thermal target and the background, and keeps the details of the background, which is more consistent with human vision perception. © 2018 IEEE.

关键词： image fusion

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Automatic flower and visitor detection system 26

Automatic flower and visitor detection system

引用

26th European Signal processing conference, EUSIPCO 2018

作者： Tran, Dat Thanh Høye, Toke Thomas Gabbouj, Moncef Iosifidis, Alexandros Laboratory of Signal Processing Tampere University of Technology Finland Department of Bioscience Aarhus University Aarhus Denmark Department of Engineering Electrical and Computer Engineering Aarhus University Denmark

ISBN: (纸本)9789082797015

The visit patterns of insects to specific flowers at specific times during the diurnal cycle and across the season play important roles in pollination biology. Thus, the ability to automatically detect flowers and visitors occurring in video sequences greatly reduces the manual human efforts needed to collect such data. Data-dependent approaches, such as supervised machine learning algorithms, have become the core component in several automation systems. In this paper, we describe a flower and visitor detection system using deep Convolutional Neural Networks (CNN). Experiments conducted in image sequences collected during field work in Greenland during June-July 2017 indicate that the system is robust to different shading and illumination conditions, inherent in the images collected in the outdoor environments. © EURASIP 2018.

关键词： Deep neural networks

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A video processing Based Eye Gaze Recognition Algorithm for Wheelchair Control

A Video Processing Based Eye Gaze Recognition Algorithm for ...

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IEEE International conference on Dependable systems, Services and Technologies (DESSERT)

作者： Sudhir Rao Rupanagudi Varsha G. Bhat Shreya K. Gurikar S. Pranava Koundinya Sumedh Kumar M. S. Shreyas R. Shilpa S. Suman N.M. Rachana R. Bademi Manisha Koppisetti Vasanthi Satyananda WorldServe Education Bangalore India Sai Vidya Institute of Technology Bangalore India Gopalan College of Engineering & Management Bangalore India Atria Institute of Technology Bangalore India

Over the past few years, a lot of research has been carried out in eye gaze recognition and its applications. From controlling wheelchairs to selecting options on a screen, utilizing the gaze of an individual has become a long-sought way for performing these tasks and in turn making the life of several differently abled people easy. In this paper a novel methodology to perform iris segmentation and gaze recognition has been introduced and described. The method elaborated utilizes a segmentation algorithm which can successfully extract the iris under varying lighting conditions with the help of machine learning. All experiments were conducted using the MATLAB R2013a software and a speed improvement of almost 3.433 times was achieved as opposed to other popular methods of iris extraction. In terms of accuracy, the algorithm proved to be 86% accurate and was also adopted to control an actual wheelchair.

关键词： Iris recognition Iris Wheelchairs image segmentation Cameras Machine learning algorithms image color analysis

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Low-Cost Wearable Technology Model to Control and Monitor Chronic Diseases for Healthcare 25

Low-Cost Wearable Technology Model to Control and Monitor Ch...

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25th IEEE International conference on Electronics, Electrical Engineering and Computing (INTERCON)

作者： Pumajulca-Salazar, Alcibiades Mac-Choy, Jorge Armas-Aguirre, Jimmy Univ Peruana Ciencias Aplicadas Informat Syst Engn Lima Peru

ISBN: (纸本)9781538654903

In this paper, we propose a low-cost wearable technology model to control and monitor chronic diseases for healthcare. We enhance prior models by focusing on low cost components, and we assess the current hardware and systems applications offered in the market. Our proposed model also emphasizes the application of real-time data analysis for the healthcare organization. The model consists of six components: 1. Data acquisition;2. Data processing;3. Information Results;4. Decision making Support;5. Technology Platform;6. Framework for personal data protection. The model was validated with a group of 12 females over 70 years who were diagnosed with tumors at different stages. The preliminary results show that the mean temperature difference between the armpits and malignant tumors is 0.7 +/- 0.5, while the mean temperature difference between the armpits and benign tumors is 2.1 +/- 0.5.

关键词： Low-Cost Wearable Chronic Disease Tumor algorithms and Complexity Intelligent systems Social Issues and Professional Practice Signal and image processing Control systems

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A novel method for the extraction of primary visual features from an image through intelligent feature descriptors

A novel method for the extraction of primary visual features...

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2017 International conference on Recent Innovations in Signal processing and Embedded systems, RISE 2017

作者： Deshpande, Abhinav V. Subashini, M. Monica School of Electronics Engineering V. I. T. University Vellore India

ISBN: (纸本)9781509047604

As far as the safety of a driver is concerned, more focus should be put on correct interpretation and information which is conveyed by a traffic sign, while driving a vehicle along the road. A sign board can be thought of as an emblem which disseminates important and meaningful information regarding the potential hazards prevailing among road users comprising roadways cladded with snowfall, construction worksites or repairing of roads taking place and telling the people to follow an alternative route. It alerts the person who is passing through the road about the maximum possible extremity that his vehicle is trying to achieve indicating slowing down the speed of vehicle since chances of having collision cannot be ruled out. With constant increasing of the training database size, not only there cognition accuracy, but also the computation complexity should be considered in designing a feasible recognition approach. The traffic sign images were acquired from the image database and were subjected to some pre-processing techniques such as conversion of the original RGB images into HSV Color Space, Adjustment of the Contrast of the Color images as well as applying the Histogram of Oriented Gradients (HOG) algorithm in which the process of extraction and plotting of the HOG features from a given image is performed that is most popular amongst the feature extraction algorithms. In the future, we will concentrate on detecting, recognizing as well as classifying a particular sign board. © 2017 IEEE.

关键词： Vehicles

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