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检索条件"任意字段=Conference on Parallel and Distributed Methods for Image Processing"

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Flexible distributed systems for multimedia applications

Flexible distributed systems for multimedia applications

引用

6th International conference on parallel and distributed Systems (ICPADS98)

作者： Kanezuka, T Higaki, H Takizawa, M Tokyo Denki Univ Dept Syst & Comp Engn Tokyo Japan

ISBN: (纸本)0818686030

This paper discusses how to make a distributed object system flexible so as to satisfy applications' requirements in change of the system environment. The system change is modeled to be the change of not only types of service but also quality of service (QoS) supported by the objects. There are two types of methods changing the objects, one for manipulating the states of the objects and another for changing QoS of the objects. We discuss new relations among methods with respect to QoS. By using the QoS-based relations, we newly discuss a QoS-based compensating way to recover the abject from the less qualified state.

关键词： distributed computer systems

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parallel and distributed methods for image retrieval with dynamic feature extraction on cluster architectures 12

Parallel and distributed methods for image retrieval with dy...

引用

12th International conference on Database and Expert Systems Applications (DEXA)

作者： Kao, O Tech Univ Clausthal Dept Comp Sci D-38678 Clausthal Zellerfeld Germany

ISBN: (纸本)0769512305

The ongoing production of Petabytes of multimedia data per year creates, an urgent need for the organisation, management, and retrieval of multimedia information. Related memory. bandwidth, and computational requirements, often surpass the capabilities of traditional database systems and computer architectures. Moreover, improved retrieval techniques allow a manual selection of regions of interest, which are subsequently searched in all media in the database by using, dynamically extracted features. This paper presents techniques for parallel multimedia retrieval by considering an image database as, an example. The discussed cluster architecture depicts one, possible solution for the performance problem. The distribution of the image data over a large number of nodes enables a parallel processing of the compute intensive operations for dynamic image retrieval. Thus, the partitioning of the data and the, applied strategies for workload balancing have a decisive impact on the performance,, efficiency, and the usability of such image databases.

关键词： Art Computer architecture Data mining Feature extraction image databases image processing image retrieval Information retrieval Multimedia databases Multimedia systems

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Stream processing of Scientific Big Data on Heterogeneous Platforms - image Analytics on Big Data in Motion

Stream Processing of Scientific Big Data on Heterogeneous Pl...

引用

IEEE 16th International conference on Computational Science and Engineering (CSE)

作者： Najmabadi, S. M. Klaiber, M. Wang, Z. Baroud, Y. Simon, S. Univ Stuttgart Inst Parallel & Distributed Syst D-70174 Stuttgart Germany

High performance image analytics is an important challenge for big data processing as image and video data is a huge portion of big data e.g. generated by a tremendous amount of image sensors worldwide. This paper presents a case study for image analytics namely the parallel connected component labeling (CCL) which is one of the first steps of image analytics in general. It is shown that a high performance CCL implementation can be obtained on a heterogeneous platform if parts of the algorithm are processed on a fine grain parallel field programmable gate array (FPGA) and a multicore processor simultaneously. The proposed highly efficient architecture and implementation is suitable for the processing of big image and video data in motion and reduces the amount of memory required by the hardware architecture significantly for typical image sizes.

关键词： component Big data image analytic stream processing image processing heterogeneous platform feature extraction data in motion component labeling

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A Fast Robustness Quantification Method for Evaluating Typical Deep Learning Models by Generally image processing 18

A Fast Robustness Quantification Method for Evaluating Typic...

引用

18th IEEE Int Symp on parallel and distributed Proc with Applicat (ISPA) / 10th IEEE Int Conf on Big Data and Cloud Comp (BDCloud) / IEEE Int Symp on Social Comp and Networking (SocialCom) / IEEE Int Conf on Sustainable Comp and Commun (SustainCom)

作者： Li, Haocong Cheng, Yunjia Ren, Wei Zhu, Tianqing China Univ Geosci Sch Comp Sci Wuhan Peoples R China Guangxi Key Lab Cryptog & Informat Secur Guilin Peoples R China Chinese Acad Sci CAS Inst Informat Engn Key Lab Network Assessment Technol Beijing 100093 Peoples R China

ISBN: (纸本)9781665414852

Deep learning especially image recognition techniques have been extensively used in various applications such as unmanned driving. The robustness of deep learning models is of critical importance since fault image recognition results may result in serious incidents. In this paper, we propose a fast quantifying method by general image processing to evaluate the robustness of five typical deep learning models under the Keras framework (i.e., VGG16, InceptionV3, ResNet50, DenseNet, and MobileNet). We analyze six metrics in terms of accuracy, precision, recall, F1, recognition time, and impact factor. The evaluation data is publicly accessible image data sets from Kaggle. In our evaluation, the adversary samples are generated by generally image processing methods such as gray-scaling, color-reversing, and image-flipping, which is ordinary operations and easily launched. The different models over various image processing methods are evaluated and compared comprehensively. The evaluation results show that DenseNet performs best over three conditions such as baseline, gray-scaling and horizontal flipping. MobileNet costs the shortest delay in decision over all image processing methods. F1 score varies with different attack intensity. InceptionV3 presents overall robustness in most conditions.

关键词： robustness model evaluation deep learning image recognition

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Performance Prediction of distributed Applications Using Block Benchmarking methods

Performance Prediction of Distributed Applications Using Blo...

引用

19th International Euromicro conference on parallel, distributed and Network-Based processing (PDP)

作者： Cornea, Bogdan Florin Bourgeois, Julien Univ Franche Comte LIFC 1 Cours Leprince Ringuet F-25201 Montbeliard France

ISBN: (纸本)9780769543284

An ongoing work is presented for accurately predicting the performance of distributed applications in heterogeneous systems. We are developing dPerf, a tool built using the Rose framework for performing static analysis and an automatic instrumentation on the input source code of programs written in C, C++ or Fortran. The accuracy in predicting program computation time resides in using hardware counters, as well as in applying two block benchmarking techniques that we propose in this paper. The current work makes use of a network simulator in order to calculate the communication time used in our approach. Afterwards, the computation and communication times are being summed up obtaining an estimation of the distributed application execution time. The approach is proven experimentally using NAS Integer Sort benchmark, the communications being simulated with SimGrid.

关键词： dPerf performance prediction block benchmarking static analysis trace-based simulation heterogeneous systems MPI P2PSAP

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Issues in implementing block-based image compression techniques on parallel MIMD architectures

Issues in implementing block-based image compression techniq...

引用

1997 conference on Visual Communications and image processing

作者： Uhl, A Hammerle, J Univ. Salzburg (Austria)

ISBN: (纸本)0819424358

Although block-based image compression techniques seem to be straightforward to implement on parallel MIMD architectures, problems might arise due to architectural restrictions on such parallel machines (e.g. memory constraints on distributed memory architectures). In this paper we discuss possible solutions to such problems occurring in different image compression techniques. Experimental results are included for adaptive wavelet block coding and fractal compression.

关键词： image compression parallel algorithms MIMD architectures

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Integrating Unsupervised and Supervised Clustering methods on a GPU platform for Fast image Segmentation

Integrating Unsupervised and Supervised Clustering Methods o...

引用

3rd International conference on image processing Theory, Tools and Applications (IPTA)

作者： Faro, Alberto Giordano, Daniela Palazzo, Simone Univ Catania Dept Elect Elect & Comp Engn I-95124 Catania Italy

ISBN: (纸本)9781467325851;9781467325837

Aim of the paper is to demonstrate how by integrating unsupervised and supervised parallel neural clustering methods in a GPU platform we may carry out a fast image segmentation with a satisfactory compromise between the topological preservation of the original image and the minimization of the quantization error, also known as clustering accuracy. For this reason, an unsupervised parallel clustering method inspired by the Extended SOM (ESOM) powered by a Learning Vector Quantization (LVQ) like algorithm is proposed. Then, its parallel supervised versions is presented to further minimize the quantization error in case proper prototypes of the desired clusters are known. Finally, the GPU implementation of both these methods are illustrated to show how we may support time critical tasks such as real time surveillance, interactive medical diagnosis, and control of dynamical systems. The performance of the GPU implementation is discussed with the help of small examples and realistic processing tasks.

关键词： image segmentation parallel Clustering GPU Implementation

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ProTailor: a parallel Operator for Extremely Fast Shape Analysis in Bioinformatics Applications

ProTailor: a Parallel Operator for Extremely Fast Shape Anal...

引用

17th Euromicro International conference on parallel, distributed and Network-Based processing

作者： Mortara, Michela Galizia, Antonella CNR Ist Matemat Applicata & Tecnol Informat Genoa Italy

ISBN: (纸本)9780769535449

The geometric shape of molecular surfaces strongly influences the docking processes where, although electrostatic, hydrophobic and van der Waals interactions affect greatly the binding affinity of the molecules, shape complementarity is a necessary condition. The vast majority of molecular docking algorithms uses a brute force enumeration of the transformation space, which requires extremely long running times. Few other methods use local shape feature matching to reduce the search to those relative positions which satisfy geometric constraints. Based on a shape analysis tool developed in Computer Graphics, in this paper we introduce ProTailor, a parallel algorithm for efficient multi-scale detection of morphological features on molecular surfaces. Thanks to an almost linear speed-up, we show how ProTailor is well suited to efficiently identify salient features like cavities and depressions, saddle areas or bridges. Feature identification may serve as a powerful tool to automatically locate potential binding sites or as a pre-processing step for efficient shape complementarity assessment in docking prediction.

关键词： shape analysis curvature evaluation parallel computing bioinformatics

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Stereo Matching by Using Self-distributed Segmentation and Massively parallel GPU Computing 15th

Stereo Matching by Using Self-distributed Segmentation and M...

引用

15th International conference on Artificial Intelligence and Soft Computing (ICAISC)

作者： Qiao, Wenbao Creput, Jean-Charles Univ Technol Belfort Montbeliard IRTES SET Belfort France

ISBN: (纸本)9783319393841

As an extension of using image segmentation to do stereo matching, firstly, by using self-organizing map (som) and K-means algorithms, this paper provides a self-distributed segmentation method that allocates segments according to image's texture changement where in most cases depth discontinuities appear. Then, for stereo, under the fact that the segmentation of left image is not exactly same with the segmentation of right image, we provide a matching strategy that matches segments of left image to pixels of right image as well as taking advantage of border information from these segments. Also, to help detect occluded regions, an improved aggregation cost that considers neighbor valid segments and their matching characteristics is provided. For post processing, a gradient border based median filter that considers the closest adjacent valid disparity values instead of all pixels' disparity values within a rectangle window is provided. As we focus on real-time execution, these time-consumming works for segmentation and stereo matching are executed on a massively parallel cellular matrix GPU computing model. Finaly, we provide our visual dense disparity maps before post processing and final evaluation of sparse results after post-processing to allow comparison with several ranking methods top listed on Middlebury.

关键词： Stereo image segmentation SOM Self-distributed segments

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Coherent Application Delivery on Hybrid distributed Computing Infrastructures of Virtual Machines and Docker Containers 25

Coherent Application Delivery on Hybrid Distributed Computin...

引用

25th Euromicro International conference on parallel, distributed and Network-Based processing (PDP)

作者： Molto, German Caballer, Miguel Perez, Alfonso de Alfonso, Carlos Blanquer, Ignacio Univ Politecn Valencia Ctr Mixto CSIC I3M CIEMAT Camino Vera S-N E-46022 Valencia Spain

ISBN: (纸本)9781509060580

There is an opportunity for distributed Computing Infrastructures (DCIs) to embrace container-based virtualisation to support efficient execution of scientific applications without the performance penalty commonly introduced by Virtual Machines (VMs). However, containers (e.g. Docker) and VMs feature different image formats and disparate procedures for deployment and management, thus hindering the adoption of hybrid DCIs (HDCIs) comprised of those kind of resources. This paper describes a workflow based on open-source tools and standards to introduce coherent application delivery on HDCIs in which applications require to be deployed on both VMs and Docker containers. Leveraging and extending the TOSCA standard to describe application requirements, and adopting DevOps practices, resulted in the coherent creation of the artifacts required for the execution of the applications on different platforms. The paper features the adoption of this approach in the INDIGO-DataCloud project.

关键词： Cloud Computing distributed Infrastructures Containers Docker Scientific Computing

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