The aim of the paper is to validate a software architecture that allows an image processing researcher to develop parallelapplications. The challenge was to develop algorithms that perform real-time low level operati...
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ISBN:
(纸本)9789604741762
The aim of the paper is to validate a software architecture that allows an image processing researcher to develop parallelapplications. The challenge was to develop algorithms that perform real-time low level operations on digital images able to be executed on a cluster of desktop PCs. The experiments show how to use parallelizable patterns and how to optimize the load balancing between the workstations.
We consider the development and implementation of eigensolvers on distributed memory parallel arrays of vector processors and show that the concomitant requirements for vectorisation and parallelisation lead both to n...
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Frequent items detection is one of the valuable techniques in many applications, such as network monitor, network intrusion detection, worm virus detection, and so on. This technique has been well studied on determini...
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ISBN:
(纸本)9783642173158
Frequent items detection is one of the valuable techniques in many applications, such as network monitor, network intrusion detection, worm virus detection, and so on. This technique has been well studied on deterministic databases. However, it is a new task on emerging uncertain database, especially in distributed environment. In this paper, a new definition of frequent items on uncertain data is defined. Based on the definition, a polynomial algorithm is proposed, which can efficiently answer the queries in central environment. Furthermore, this work designs the communication-efficient algorithms for retrieving the top-k items with the largest probability from distributed sites. The algorithms compute the upper bound of each round of the transmission, and filter the data as much as possible, which have no chance to influence the query result. Extensive experiments show that the algorithms can process the queries correctly and reduce communication cost efficiently with various data set.
The two-volume set LNCS 6852/6853 constitutes the refereed proceedings of the 17th international Euro-Par conference held in Bordeaux, France, in August/September 2011.The 81 revised full papers presented were careful...
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ISBN:
(数字)9783642233975
ISBN:
(纸本)9783642233968
The two-volume set LNCS 6852/6853 constitutes the refereed proceedings of the 17th international Euro-Par conference held in Bordeaux, France, in August/September 2011.
The 81 revised full papers presented were carefully reviewed and selected from 271 submissions. The papers are organized in topical sections on support tools and environments; performance prediction and evaluation; scheduling and load-balancing; high-performance architectures and compilers; parallel and distributed data management; grid, cluster and cloud computing; peer to peer computing; distributed systems and algorithms; parallel and distributed programming; parallel numerical algorithms; multicore and manycore programming; theory and algorithms for parallel computation; high performance networks and mobile ubiquitous computing.
This paper presents super-threading, which generically means the architectural and software mechanisms for optimizing parallel computation. Super-threading includes architectural optimization of a processing element (...
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Modern HPC systems are constructed by placing more and more cores in a single machine. To utilize this kind of machines efficiently, many parallel processes have to be used. The performance analysis of massively paral...
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In recent networked world, more of the times computers work not isolation. They work with each other in order to satisfy communication purpose, processing, transfer of data, saving, etc., the systems can be described ...
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In this work, we study one of the major problems in exploring the power of GPUs to accelerate video processingapplications: countless frames have to be transferred back and forth between the CPU and GPU. We evaluate ...
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distributed Virtual Environment (DVE) systems have become more and more important both in academic communities and the industries. To guarantee the load constrain, the physical world integrity and the virtual world in...
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Handwritten signatures hold paramount importance in legal, financial, and administrative domains, necessitating the development of robust signature recognition tools for forensic applications. This paper introduces a ...
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ISBN:
(纸本)9798350373981;9798350373974
Handwritten signatures hold paramount importance in legal, financial, and administrative domains, necessitating the development of robust signature recognition tools for forensic applications. This paper introduces a handwritten signature recognition (HSR) model employing parallel Convolutional Neural Networks (CNN) tailored for forensic endeavors. Utilizing the parallelprocessing capabilities of CNN, our proposed approach adeptly analyzes and extracts discriminative features from handwritten signature images to facilitate precise recognition. In addition, we leverage several transfer learning techniques by parallelizing proven pre-trained CNNs. Extensive experimentation validates the efficacy of our approach on a standard dataset, demonstrating high accuracy and resilience in signature recognition tasks. The proposed approach exhibits substantial promise in augmenting forensic investigations by automating signature verification processes, thereby bolstering fraud detection efforts and upholding the integrity of legal documentation.
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