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检索条件"机构=Image Processing and Computer Graphics Department"

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Testing cross-platform streaming of video games over wired and wireless LANs

Testing cross-platform streaming of video games over wired a...

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24th IEEE International Conference on Advanced Information Networking and Applications Workshops, WAINA 2010

作者： Jurgelionis, A. Bellotti, F. De Gloria, A. Laulajainen, J.-P. Fechteler, P. Eisert, P. David, H. Department of Biophysical and Electronic Engineering University of Genoa Genoa Italy Converging Networks Laboratory VTT Technical Research Centre of Finland Oulu Finland Computer Vision and Graphics Image Processing Department Heinrich-Hertz-Institute Fraunhofer-Institute for Telecommunications Berlin Germany R and D Department Exent Technologies Ltd. Petach Tikva Israel

ISBN: (纸本)9780769540191

In this paper we present a new cross-platform approach for video game delivery in wired and wireless local networks. The developed 3D streaming and video streaming approaches enable users to access video games on set top boxes and handheld devices that natively are not capable to run PC games. During the development of the distributed gaming system we have faced a number of challenges and problems posed by the hardware and network limitations. In order to solve these problems we have developed a multilevel testing methodology which is based on user assessment and technical measures for the system under development. In this paper we focus on the technical measures and instrumentation that we use for the system's performance measurement and testing. The benefits of our testing methodology are demonstrated through examples from the development and testing work. © 2010 IEEE.

关键词： Human computer interaction

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Operators to dilate and erode color impulse noise images based on the morphology

Operators to dilate and erode color impulse noise images bas...

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International Conference on E-Business and E-Government (ICEE)

作者： Ah Yin Xing-yun Research direction: Digital Image Processing Computer Graphics Computer and Information Engineering Department Huainan Normal University Huainan 232038 P. R. China

By analyzing the numerical characteristics of impulse noise images, in order to resolve spreading-noise problem resulted from dilating and eroding images base on mathematical morphology, an algorithm of dilating and eroding color impulse noise images based on mathematical morphology is proposed. The result of the experiment demonstrates that the new algorithm has same effect as traditional algorithm of dilating and eroding images, but also suppresses impulse noise.

关键词： Niobium image color analysis Morphology computers Colored noise Machine vision

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An extended probabilistic collaborative representation based classifier for image classification

An extended probabilistic collaborative representation based...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Rushi Lan Yicong Zhou Key Laboratory of Intelligent Processing of Computer Image and Graphics Guilin University of Electronic Technology Guilin China Department of Computer and Information Science University of Macau Macau China

ISBN: (纸本)9781509060689

Collaborative representation based classifier (CRC) and its probabilistic improvement ProCRC have achieved satisfactory performance in many image classification applications. They, however, do not comprehensively take account of the structure characteristics of the training samples. In this paper, we present an extended probabilistic collaborative representation based classifier (EProCRC) for image classification. Compared with CRC and ProCRC, the proposed EProCRC further considers a prior information that describes the distribution of each class in the training data. This prior information enlarges the margin between different classes to enhance the discriminative capacity of EProCRC. Experiments on two challenging databases, namely CUB200-2011 and Caltech-256, are conducted to evaluate EProCRC, and comparison results demonstrate that it outperforms several state-of-the-art classifiers.

关键词： Training Collaboration Probabilistic logic Training data Feature extraction Databases Robustness

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Convolutional Neural Network For Predicting The Spread of Cancer

Convolutional Neural Network For Predicting The Spread of Ca...

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International Conference on Cognitive Infocommunications (CogInfoCom)

作者： Oktavian Lantang Attila Tiba Andras Hajdu Gyorgy Terdik Department of Applied Information Technology and its Theoretical Background University of Debrecen Debrecen Hungary Department of Computer Graphics and Image Processing University of Debrecen Debrecen Hungary

ISBN: (数字)9781728147932

ISBN: (纸本)9781728147949

Detecting the spread of cancer using digital images requires expertise from a pathologist, takes time and vulnerable to human error. In our work, we offer an approach to using a convolutional neural network (CNN) to predict the presence of cancer by using pathological images. We have developed a CNN framework, applied data augmentation then trained our model using a single GPU (Graphic Processor Unit) provided by Google Collaborator. We have used data published in the form of a Kaggle dataset. Datasets are small pathology images which are derived from Camelyon16, namely PatchCam. This database consists of approximately 200,000 images categorized into two classes: cancer and no cancer. We have split the data with a proportion of 70% for training and 30% for validation. We can report satisfactory results regarding the 200,000 images in the training and validation processes with accuracy reaches 0.92. The fl scores have found to be 0.94 for class no cancer and 0.91 for class cancer, while the AUC grade has 0.98. Besides the presentation of competitive results, we discuss how such automatic systems may improve the cognitive capabilities of clinical experts.

关键词： Cancer Feature extraction Training Convolutional neural networks computer architecture Error analysis Data models

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FAST ALGORITHM FOR COMPUTING FRACTAL DIMENSIONS OF image SEGMENTS

FAST ALGORITHM FOR COMPUTING FRACTAL DIMENSIONS OF IMAGE SEG...

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SATELLITE CONF AT THE 1988 BIANNUAL INTERNATIONAL CONF ON PATTERN RECOGNITION : RECENT ISSUES IN PATTERN ANALYSIS AND RECOGNITION

作者： CREUTZBURG, R IVANOV, E Central Institute of Cybernetics and Information Processes International Basic Laboratory for Image Processing and Computer Graphics Academy of Sciences of the G.D.R. Kurstr. 33 P. O. Box 1298 Berlin DDR - 1086 Germany Department of Information Techniques University of Technology Mommsenstr. 13 Dresden DDR - 8027 Germany

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Knee-joint tissue recognition in magnetic resonance imaging

Knee-joint tissue recognition in magnetic resonance imaging

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IEEE Neumann Colloquium (NC)

作者： Artjoms Suponenkovs Zigurds Markovics Ardis Platkajis Department of Image Processing and Computer Graphics Riga Technical University Riga Latvia Systems of Computer Control department Riga Technical University Riga Latvia Department of Radiology Riga Stradins University Riga Latvija

ISBN: (纸本)9781538646373

The automatic knee-joint soft tissue recognition problem is very relevant due to increasing number of people with knee-joint diseases. It is for this reason that this paper investigates the problem of soft tissue recognition in magnetic resonance imaging (MRI). MRI is useful for knee-joint soft tissue presentation, but usually a doctor cannot see all necessary information in MRI data. computer MRI analysis makes it possible to process all MRI data and shows additional information for the doctor. This additional information can make it easier to detect invisible injuries of knee-joint soft tissues. Knee-joint soft tissue recognition and analysis are very helpful, especially for osteoarthritis (OA) early diagnostics. computer OA diagnostics are impossible without segmentation of knee-joint tissues. This publication describes approaches for knee-joint image pre-processing, knee-joint image segmentation, tissue recognition and tissue analysis. To solve tissue analysis task it is important to use biological information of knee-joint structure, physical and biochemical tissue features. Tissue analysis is very useful especially for early diagnostics. It allows starting treatment earlier and therefore reducing the risk of tissue destruction. It is for this reason that this paper investigates the above-mentioned challenges.

关键词： image segmentation Biological tissues Filtering image recognition Medical services DICOM

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Sampling step importance in hierarchical semantic segmentation of microscopic images

Sampling step importance in hierarchical semantic segmentati...

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International Conference on System Theory, Control, and Computing (ICSTCC)

作者： Cristian Smochina Vasile Manta Walter Kropatsch Department of Computer Science and Engineering Gheorghe Asachi Technical University of Iasi Romania Pattern Recognition and Image Processing Group Institute of Computer Graphics and Algorithms Vienna University of Technology Austria

The objective of semantic segmentation in microscopic images is to extract the cellular, nuclear or tissue components. This problem is challenging due to the large variations of these components features (size, shape, orientation or texture). In this paper we improve the technique presented in [17] used to identify the epithelial nuclei (crypt) against interstitial nuclei in microscopic images taken from colon tissues. In the proposed enhanced approach, the crypt inner boundary is detected using the closing morphological pyramid instead of morphological hierarchy. The outer crypt border is determined by the epithelial nuclei, overlapped by the maximal isoline of the inner boundary. The use of sampling in building the pyramid offers computational efficiency, reduces the amount of used memory, increase the robustness and preserve the quality results. An analysis of the two approaches is performed considering the number of pixels processed to create each level. Also the relation between the levels of the hierarchical structures is established.

关键词： Cryptography image segmentation image reconstruction image resolution Microscopy Buildings Shape

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Visual analysis of multi-joint kinematic data

Visual analysis of multi-joint kinematic data

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12th Eurographics/IEEE-VGTC Symposium on Visualization, EuroVis 2010

作者： Krekel, Peter R. Valstar, Edward R. De Groot, Jurriaan Post, Frits H. Nelissen, Rob G. H. H. Botha, Charl P. Biomechanics and Imaging Group Leiden University Medical Center Netherlands Computer Graphics Delft University of Technology Netherlands Department of Rehabilitation Medicine Leiden University Medical Center Netherlands Divison of Image Processing Leiden University Medical Center Netherlands Biomechanical Engineering Delft University of Technology Netherlands

Kinematics is the analysis of motions without regarding forces or inertial effects, with the purpose of understanding joint behaviour. Kinematic data of linked joints, for example the upper extremity, i.e. the shoulder and arm joints, contains many related degrees of freedom that complicate numerical analysis. Visualisation techniques enhance the analysis process, thus improving the effectiveness of kinematic experiments. This paper describes a new visualisation system specifically designed for the analysis of multi-joint kinematic data of the upper extremity. The challenge inherent in the data is that the upper extremity is comprised of five cooperating joints with a total of fifteen degrees of freedom. The range of motion may be affected by subtle deficiencies of individual joints that are difficult to pinpoint. To highlight these subtleties our approach combines interactive filtering and multiple visualisation techniques. Our system is further differentiated by the fact that it integrates simultaneous acquisition and visual analysis of biokinematic data. Also, to facilitate complex queries, we have designed a visual query interface with visualisation and interaction elements that are based on the domain-specific anatomical representation of the data. The combination of these techniques form an effective approach specifically tailored for the investigation and comparison of large collections of kinematic data. This claim is supported by an evaluation experiment where the technique was used to inspect the kinematics of the left and right arm of a patient with a healed proximal humerus fracture, i.e. a healed shoulder fracture. © The Eurographics Association and Blackwell Publishing Ltd.

关键词： Kinematics

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OPTIMAL PARALLEL CONFLICT-FREE ACCESS TO EXTENDED BINARY-TREES

OPTIMAL PARALLEL CONFLICT-FREE ACCESS TO EXTENDED BINARY-TRE...

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SATELLITE CONF AT THE 1988 BIANNUAL INTERNATIONAL CONF ON PATTERN RECOGNITION : RECENT ISSUES IN PATTERN ANALYSIS AND RECOGNITION

作者： CREUTZBURG, R ANDREWS, L Central Institute of Cybernetics and Information Processes International Basic Laboratory for Image Processing and Computer Graphics Academy of Sciences of the G.D.R. Kurstrasse 33 P.O.Box 1298 Berlin DDR - 1086 Germany Department of Mathematics Humboldt-University of Berlin Unter den Linden 6 P.O.Box 1297 Berlin DDR - 1086 Germany

In this paper the parallel conflict-free access to complete extended binary subtrees of complete binary trees is investigated. Thereby linear and also nonlinear memory module assignment functions S are considered. Fur... 详细信息

ISBN: (纸本)0387518150

关键词： Binary trees

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A New image Quality Measure

A New Image Quality Measure

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IEEE Canadian Conference on Electrical and computer Engineering

作者： Saif alZahir Faramarz Kashanchi Image Processing and Graphics Lab Computer Science Department UNBC

ISBN: (纸本)9781479900312

Measuring image quality is an interesting and challenging area of research. In this paper we investigate the performance of the statistical functions called copula as image quality measures. These functions are popular for applications where data distributions are unknown. This property motivated some researchers to using these copulas in image processing in general and in detecting image changes and image registration in particular. In this research, we use the Gaussian copula to calculate the mutual information, which is the measure of the association of the reference and the distorted or tampered with images. To test the performance of the proposed method, we implemented our method on LIVE image database and compared our results with three popular image quality measures namely Visual Information Fidelity (VIF), Structural Similarity (SSIM), and Universal Quality Measure (UQI). The results show that our quality measure, obtained similar results to the three methods in 99% of the time, hence the proposed method can be considered as an efficient image quality index.

关键词： image quality measure VIF SSIM UQI Gaussian copula

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