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检索条件"任意字段=18th Image Processing: Algorithms and Systems Conference, IPAS 2020"

共 256 条记录，以下是111-120 订阅

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Micro-CT-based analysis of fibre-reinforced composites: Applications 18

Micro-CT-based analysis of fibre-reinforced composites: Appl...

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18th European conference on Composite Materials, ECCM 2018

作者： Straumit, I. Baran, I. Gorbatikh, L. Farkas, L. Hahn, C. Ilin, K. Ivens, J. Lessard, L. Liu, Y. Nguyen, N. Matveeva, A. Mehdikhani, M. Shishkina, O. Soete, J. Takahashi, J. Vandepitte, D. Vasiukov, D. Wan, Y. Winterstein, E. Wevers, M. Lomov, S.V. Department of Materials Engineering KU Leuven Belgium Chair of Production Technology Faculty of Engineering Technology University of Twente Netherlands Siemens Industry Software NV Leuven Belgium Germany Department of Mechanical Engineering McGill University Montreal Canada Polymers and Composites Technology and Mechanical Engineering Department IMT Lille Douai France SIM M3 program Technologiepark 935 ZwijnaardeB-9052 Belgium Department of Systems Innovation University of Tokyo Japan Department of Mechanical Engineering KU Leuven Belgium

ISBN: (纸本)9781510896932

the paper presents an overview of cases in which the analysis of the internal structure and mechanical properties of fibre reinforced composites is performed based on the micro-computed X-ray tomography (micro-CT) reconstruction of the composite reinforcement geometry. In all the cases, the analysis relies on structure tensor-based algorithms for quantification of the micro-CT image, implemented in VoxTex software. © CCM 2020 - 18th European conference on Composite Materials. All rights reserved.

关键词： Computerized tomography

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A CAD System for Brain Haemorrhage Detection in Head CT Scans 18

A CAD System for Brain Haemorrhage Detection in Head CT Scan...

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18th IEEE International conference on Smart Technologies (IEEE EUROCON)

作者： Napier, John Debono, Carl James Bezzina, Paul Zarb, Francis Univ Malta Dept Commun & Comp Engn MSD-2080 Msida Malta Univ Malta Dept Radiog MSD-2080 Msida Malta

ISBN: (纸本)9781538693018

Medical imaging is an important medical diagnostic tool that provides visual information of the interior of the human body. In recent years computer-aided detection/diagnosis (CAD) systems became a key component of routine clinical practice in several medical areas, such as mammography and colonoscopy. However, research on brain CAD systems is still limited compared to other areas. this paper presents a solution that uses image processing techniques on brain computed tomography (CT) scans to create a CAD system that detects fresh bleeds. the system also features a basic classification method that distinguishes between an intra-axial and an extra-axial haemorrhage with the only limitation being subarachnoid haemorrhage (SAH), which is not always properly classified due to its complex structure. the techniques implemented include noise reduction methods, morphological operations and segmentation algorithms. the developed CAD system was tested on 36 brain CT sets obtained from the general hospital in Malta. Results show that the system achieves a sensitivity of 94.4 %, a specificity of 94.4%, a precision of 91.259% and a classification accuracy of 88.89%.

关键词： Computer-aided diagnosis computed tomography image processing medical imaging

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Adaptation of parameterized interpolation algorithms of multidimensional signals for hierarchical and interpolation compression methods 6

Adaptation of parameterized interpolation algorithms of mult...

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6th International conference Information Technology and Nanotechnology. Session image processing and Earth Remote Sensing, ITNT-IPERS 2020

作者： Gashnikov, Mikhail Department of GIS ITsec Samara National Research University MMIP Laboratory Image Processing Systems Institute of RAS Branch of the FSRC "Crystallography and Photonics" RAS Samara Russia

We adapt parameterized multidimensional signal interpolators for hierarchical compression methods and interpolation compression methods based on the coding of quantized post-interpolation residues. the considered interpolators automatically select the most appropriate interpolating function at each point of the signal using a parameterized decision rule. We propose a set of interpolation functions for these compression methods. We select the optimization criterion for the proposed interpolator. the optimization criterion is based on minimization the entropy of the quantized post-interpolation residues. We solve the optimization problem of the adaptive parameterized interpolator according to this criterion. We perform computational experiments to study the proposed interpolators in natural multidimensional signals. the experimental results confirm that the use of the adaptive interpolators can significantly increase the effectiveness of the mentioned methods of multidimensional signals compression. Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)

关键词： Interpolation

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Least-squares Optimal Relative Planar Motion for Vehicle-mounted Cameras

Least-squares Optimal Relative Planar Motion for Vehicle-mou...

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IEEE International conference on Robotics and Automation (ICRA)

作者： Hajder, Levente Barath, Daniel Eotvos Lorand Univ Dept Algorithms & Their Applicat Budapest Hungary Czech Tech Univ Visual Recognit Grp Dept Cybernet Prague Czech Republic MTA SZTAKI Machine Percept Res Lab Budapest Hungary

ISBN: (纸本)9781728173955

A new closed-form solver is proposed minimizing the algebraic error optimally, in the least squares sense, to estimate the relative planar motion of two calibrated cameras. the main objective is to solve the over-determined case, i.e., when a larger-than-minimal sample of point correspondences is given - thus, estimating the motion from at least three correspondences. the algorithm requires the camera movement to be constrained to a plane, e.g. mounted to a vehicle, and the image plane to be orthogonal to the ground.(1) the solver obtains the motion parameters as the roots of a 6th degree polynomial. It is validated both in synthetic experiments and on publicly available real-world datasets that using the proposed solver leads to results superior to the state-of-the-art in terms of geometric accuracy with no noticeable deterioration in the processing time.

关键词： Cameras Transmission line matrix methods Robot vision systems Estimation Automobiles Geometry

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Chameleon: image Style Transfer Based on image Classification Networks

Chameleon: Image Style Transfer Based on Image Classificatio...

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IEEE International conference on High Performance Computing and Communications (HPCC)

作者： Haobo Li Ratan Dey Lei Gong Chao Wang NYU Shanghai USTC China School of Computer Science USTC China

ISBN: (纸本)9781728176505

In recent years, deep neural networks enabled computers to extract features of images; this stimulated interest in image style transfer. Since the first NST algorithm, many schemes are proposed to accelerate the process. Yet, these methods more or less sacrifice the visual quality of the output. In this paper, we analyze two precursive algorithms and generalize the results. We propose an image Style Transfer method based on image Classification Networks. With Chameleon, we accelerate the runtime by 11 times and we show that general CNN techniques would improve the stylization process. Our work provides novel insights into the classification capacity of CNNs and demonstrates the potential of NST algorithms.

关键词： Computers Visualization Runtime High performance computing conferences Neural networks Feature extraction

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Statistical analysis of the QTMT structure: intra mode decision

Statistical analysis of the QTMT structure: intra mode decis...

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International image processing, Applications and systems conference (ipas)

作者： Naima Zouidi Amina Kessentini Fatma Belghith Nouri Masmoudi Laboratory of Electronics and Information Technology National Engineering School of Sfax Sfax Tunisia

ISBN: (数字)9781728175744

ISBN: (纸本)9781728175751

As part of their contribution to the continuous development of video technologies, International Telecommunication Union (ITU) and Moving Picture Experts Group (MPEG) created the Joint Expert Team (JVET) in order to study the potential need for the standardization of the future video coding, called Versatile Video Coding (VVC). the VVC project was aiming at outperforming the coding efficiency of the High-Efficiency Video Coding (HEVC) by 40-50% with the same perceptual quality. With the release of its final version in July 2020, VVC has demonstrated a superior coding efficiency, up to 40% [6] of bit reduction beyond HEVC. However, it introduces significant computational complexity in the encoding engine. Such complexity should be analyzed. In this paper, the distribution of intra modes is illustrated through statistical analysis in order to speed up the intra mode decision process in the VVC. Experimental results show that the VVC uses the 6 Most Probable Modes (MPM) as the most used intra modes. In addition, these commonly used intra modes are usually numerous on deeper Multi-type Tree (MT) depths unrelatedly to the Quantization Parameter (QP) but they may vary according to the video texture characteristics and the used intra coding tool, whether Multi Refrence Lines (MRL), Matrix Weighted Intra Prediction (MIP) or Intra Sub Partitions (ISP). this work can be considered as a milestone for proposing intelligent algorithms to perform fast encoding decisions in the intra prediction step.

关键词： image coding Statistical analysis Tools Prediction algorithms Encoding ITU High efficiency video coding

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Information Fusion-2-Text: Explainable Aggregation via Linguistic Protoforms 18th

Information Fusion-2-Text: Explainable Aggregation via Lingu...

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18th International conference on Information processing and Management of Uncertainty in Knowledge-Based systems, IPMU 2020

作者： Murray, Bryce J. Anderson, Derek T. Havens, Timothy C. Wilkin, Tim Wilbik, Anna Electrical Engineering and Computer Science Department University of Missouri ColumbiaMO United States College of Computing and Department of Electrical and Computer Engineering Michigan Technological University HoughtonMI United States School of Information Technology Deakin University GeelongVIC Australia Information Systems Group of the Department of Industrial Engineering and Innovation Sciences Eindhoven University of Technology Eindhoven Netherlands

ISBN: (纸本)9783030501525

Recent advancements and applications in artificial intelligence (AI) and machine learning (ML) have highlighted the need for explainable, interpretable, and actionable AI-ML. Most work is focused on explaining deep artificial neural networks, e.g., visual and image captioning. In recent work, we established a set of indices and processes for explainable AI (XAI) relative to information fusion. While informative, the result is information overload and domain expertise is required to understand the results. Herein, we explore the extraction of a reduced set of higher-level linguistic summaries to inform and improve communication with non-fusion experts. Our contribution is a proposed structure of a fusion summary and method to extract this information from a given set of indices. In order to demonstrate the usefulness of the proposed methodology, we provide a case study for using the fuzzy integral to combine a heterogeneous set of deep learners in remote sensing for object detection and land cover classification. this case study shows the potential of our approach to inform users about important trends and anomalies in the models, data and fusion results. this information is critical with respect to transparency, trustworthiness, and identifying limitations of fusion techniques, which may motivate future research and innovation. © 2020, Springer Nature Switzerland AG.

关键词： Information fusion

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DynaScale: An Intelligent image Scale Selection Framework for Visual Matching in Smart IoT

DynaScale: An Intelligent Image Scale Selection Framework fo...

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IEEE International conference on High Performance Computing and Communications (HPCC)

作者： Bo-Lung Tsai Kwei-Jay Lin Yuheng Cao Yu Meng University of California Irvine CA USA Northeastern University Shengyang China

ISBN: (纸本)9781728176505

Localization is one of the fundamental technologies to enable location-aware services in smart cities. image feature matching plays an essential role in visual-based localization for moving IoT devices to navigate in various scenes. Conventional matching pipelines have issues with finding an accurate transformation model when a pair of to-be-matched images have a huge scale difference between the views of interested objects. the paper introduces DynaScale, a general framework that integrates existing image detection and matching algorithms with constructed image pyramids for extended matching, and selects the best matching result from the image pairs of different scales. We have designed an intelligent evaluation scheme of potential transformation models based on various tests including reasonable projections, the resembled size of region proposals, and similarities of bounded descriptors. the experimental result shows that, on selected datasets, DynaScale has 1.9 times better mean matching accuracy than existing methods from 24.32% to 45.91%, and produces about twice the number of useful, correctly matched frames in a moving robot's video stream.

关键词： Location awareness Visualization Smart cities image matching Pipelines Robot vision systems Streaming media

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Age-Aware Query Evaluation for Big Data Analytics in Mobile Edge Clouds

Age-Aware Query Evaluation for Big Data Analytics in Mobile ...

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IEEE International conference on High Performance Computing and Communications (HPCC)

作者： Qiufen Xia Wenhao Ren Mingchu Li Jiankang Ren International School of Information Science and Engineering Dalian University of Technology Dalian China School of Software Dalian University of Technology Dalian China School of Computer Science and Technology Dalian University of Technology Dalian China

ISBN: (纸本)9781728176499;9781728176505

the advancement of 5G technology and extensive usage of smart devices have led to a deluge of data. It is invaluable to analyze such big data by issuing queries to derive real-time business insights for better, smarter and fact-based decisions. Timely big data analytics are crucial in many service domains, thus the age of data (AoD) required by queries is emerging as a novel metric that measures the freshness of data and evaluates the quality of data analytics. Traditional big data analytics that are performed in remote clouds cannot satisfy the AoD requirements of queries, due to the congested core networks and long transmission latency between users and clouds. the technique of mobile edge computing (MEC) is expected to reduce the age and guarantee the timeliness of queries for big data analytics, by processing data at edge cloudlets close to users. In this paper, we investigate a problem of age-aware query evaluation for big data analytics in a mobile edge cloud network. We first formulate the problem with certain data processing latency as an Integer Linear Program (ILP). We then develop an online learning algorithm for the problem with uncertain data processing latency. We finally evaluate the performance of proposed algorithms against existing studies by simulations and testbed implementations. Evaluation results show that the proposed algorithms outperform existing works by achieving 20% lower AoD.

关键词： Measurement Data analysis Query processing High performance computing conferences Big Data Real-time systems

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An Efficient Low Delay Task Scheduling Algorithm Based on Ant Colony System in Heterogeneous Environments

An Efficient Low Delay Task Scheduling Algorithm Based on An...

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IEEE International conference on High Performance Computing and Communications (HPCC)

作者： Pei Yang Jing Liu Cen Chen Yucheng Ding Chunhua Deng Zeng Zeng College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China Institute for Infocomm Research Singapore Hunan *** Interactive Entertainment Media Co. Ltd. Changsha China

ISBN: (纸本)9781728176505

Low delay is an important issue in a variety of applications on heterogeneous computing platforms. A great number of algorithms including heuristics as well as metaheuristics have been designed to minimize the completion time (i.e., makespan) of applications and achieved good results. However, the demand of high performance never stops. In this paper, we propose a new and efficient Ant-Colony based Low Delay Scheduling (ACLDS) algorithm to minimize the makespan of applications which can form directed acyclic graphs and are executed on a heterogeneous system. Simulated results show that our proposed algorithm is highly efficient in reducing makespan in comparison with state-of-the-art scheduling algorithms. For instance, the reduction ratio can be up to 15.2174% for a Fast Fourier Transform (FFT) benchmark.

关键词： Directed acyclic graph Smoothing methods Scheduling algorithms Fast Fourier transforms High performance computing Heuristic algorithms Scheduling

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