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检索条件"机构=Department of Parallel and Distributed Information Processing"

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YOLOv5_CSL_F: YOLOv5's Loss Improvement and Attention Mechanism Application for Remote Sensing Image Object Detection 3

YOLOv5_CSL_F: YOLOv5's Loss Improvement and Attention Mechan...

引用

3rd International Conference on Wireless Communications and Smart Grid, ICWCSG 2021

作者： Wang, Junhua Xiao, Tao Gu, Qinyi Chen, Qian National University of Defense Technology Laboratory of Parallel and Distributed Processing Changsha China No.61646 Troop Department of Information Beijing China

ISBN: (纸本)9781665425988

With the continuous improvement of the resolution of satellite remote sensing images and aerial remote sensing images, more and more useful data and information are obtained from remote sensing images. At the same time, compared with ordinary images, remote sensing images have the characteristics of variable directions, unbalanced categories, complex backgrounds, and difficult detection of small objects. All of these make remote sensing image object detection very challenging. In this paper, based on the deep learning framework and the YOLOv5 object detection algorithm, according to the characteristics of remote sensing images, adopting Circular Smooth Label (CSL) [1] to calculate the loss of the rotating object detection bounding box and introducing the FcaNet [2] attention mechanism to design new feature fusion modules, we propose the remote sensing image object detection algorithm YOLOv5_CSL_F. We tested the algorithm model on the DOTA dataset. Compared with the detection performance of the original YOLOv5 algorithm, our algorithm improves the detection accuracy by 0.6%. © 2021 IEEE.

关键词： Object detection

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Predicting the probability of exceeding critical system thresholds 11

Predicting the probability of exceeding critical system thre...

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11th International Conference of Programming UkrPROG, UkrPROG 2018

作者： Krammer, Peter Kvassay, Marcel Hluchý, Ladislav Researcher at the Institute of Informatics of the Slovak Academy of Sciences Bratislava Slovakia Research scientist at the Institute of Informatics of the Slovak Academy of Sciences Slovakia Head of the Department of Parallel and Distributed Information Processing Slovakia

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A resource broker for computing nodes selection in grid computing environments 3rd

引用

3rd International Conference on Grid and Cooperative Computing, GCC2004

作者： Yang, Chao-Tung Lai, Chuan-Lin Shih, Po-Chi Li, Kuan-Ching High-Performance Computing Laboratory Department of Computer Science and Information Engineering Tunghai University Taichung407 Taiwan Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Shalu Taichung433 Taiwan

ISBN: (纸本)3540235647

As Grid Computing is becoming a reality, there is a need for managing and monitoring the available resources worldwide, as well as the need for conveying these resources to the everyday user. This paper describes a resource broker with its main function as to match the available resources to the user’s needs. The use of the resource broker provides a uniform interface to access any of the available and appropriate resources using user’s credentials. The resource broker runs on top of the Globus Toolkit. Therefore, it provides security and current information about the available resources and serves as a link to the diverse systems available in the Grid. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Grid computing

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Decision tree construction for data mining on grid computing environments

Decision tree construction for data mining on grid computing...

引用

19th International Conference on Advanced information Networking and Applications, AINA 2005

作者： Yang, Chao-Tung Tsai, Shu-Tzu Li, Kuan-Ching High-Performance Computing Laboratory Department of Computer Science and Information Engineering Tunghai University Taichung City 40704 Taiwan Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Taichung County 43301 Taiwan

ISBN: (纸本)0769522491

In this paper, we present our Grid-based decision tree architecture, with the intention of applying it to both parallel and sequential algorithms. Also, we show that, based on the scope and model of data mining applied in the Grid environment as well as user equivalent perspective, Grid roles can be categorized into three types. It is our goal, through these definitions, to help software developers define clear system processes and differentiate the application scope for software applications. To, fulfill our architecture, we first apply an existing parallel decision tree algorithm (the SPRINT algorithm) to the Grid environment. The performance and differences in many other areas are compared using datasets of different sizes. The experimental results will be used for future reference and further development. © 2005 IEEE.

关键词： Data mining

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An enhanced parallel loop self-scheduling scheme for cluster environments

An enhanced parallel loop self-scheduling scheme for cluster...

引用

19th International Conference on Advanced information Networking and Applications, AINA 2005

作者： Yang, Chao-Tung Cheng, Kuan-Wei Li, Kuan-Ching High-Performance Computing Laboratory Department of Computer Science and Information Engineering Tunghai University Taichung City 40704 Taiwan Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Taichung County 43301 Taiwan

ISBN: (纸本)0769522491

In this paper, a parallel loop self-scheduling scheme for heterogeneous PC cluster systems is proposed. Though the proposed scheme does allow users to choose parameters before the execution initialization phase, there are still weaknesses that motivate us to go further with new improvements in that scheme. For instance, a decision on a fixed and monotonous parameter can easily lead to invalid schedule by using previous input information. Thus, it is proposed in this paper a new scheme, where the scheduling parameter can be adjusted dynamically and fit into most widely available computer systems, in order to provide higher overall performance. © 2005 IEEE.

关键词： Scheduling

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A high-performance computational resource broker for Grid Computing environments

A high-performance computational resource broker for Grid Co...

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19th International Conference on Advanced information Networking and Applications, AINA 2005

作者： Yang, Chao-Tung Shih, Po-Chi Li, Kuan-Ching High-Performance Computing Laboratory Department of Computer Science and Information Engineering Tunghai University Taichung City 40704 Taiwan Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Taichung County 43301 Taiwan

ISBN: (纸本)0769522491

Internet computing and grid technologies promise to change the way we tackle complex problems. They will enable large-scale aggregation and sharing of computational, data and other resources across institutional boundaries. As Grid Computing is becoming a reality, there is a need for managing and monitoring the available resources worldwide, ax well as the need for conveying these resources to the everyday user. This paper describes a resource broker with its main function as to match the available resources to the user's needs. The use of the resource broker provides a uniform interface to access any of the available and appropriate resources using user's credentials. The resource broker runs on top of the Globus Toolkit. Therefore, it provides security and current information about the available resources and serves as a link to the diverse systems available in the Grid. © 2005 IEEE.

关键词： Computer systems

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Survey of Software Environments for parallel distributed processing: parallel Programming Education on Real Life Target Systems Using Production Oriented Software Tools

Survey of Software Environments for Parallel Distributed Pro...

引用

Panhellenic Conference on Informatics (PCI)

作者： Constantinos T. Delistavrou Konstantinos G. Margaritis Parallel and Distributed Processing Laboratory Department of Applied Information University of Macedonia Thessaloniki Greece

parallel programming is the future of computer science. Now days shift to parallel processing makes it even more useful. This research effort aims at helping parallelism education on real life target systems, using production oriented software tools. On its beginning, a survey of software environments for parallel programming is presented. The surveyed software environments are categorized according to their main function. An identity is synthesized for each environment by software and project attributes. Based on it and a set of proper criteria there are selected two groups of tools, those of primary and those of secondary interest for this research. An analysis of functional characteristics is performed for both groups. From the first group an open source software environment is chosen as the basis platform that will be enriched with education oriented enhancements. The characteristics analysis is exploited for the proposal of a research and development framework. Its target is the support of parallel programming, on real life target systems, using production oriented software environments.

关键词： Informatics

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Design issues of a novel toolkit for parallel application performance monitoring and analysis in cluster and grid environments

Design issues of a novel toolkit for parallel application pe...

引用

8th International Symposium on parallel Architectures, Algorithms and Networks, I-SPAN 2005

作者： Li, Kuan-Ching Wang, Hsiao-Hsi Chen, Chiou-Nan Liu, Chun-Chieh Chang, Chia-Fu Hsu, Chia-Wen Hung, Sheng-Shiang Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Shalu Taichung 43301 Taiwan Laboratory of Bioinformatics and Computational Biology Department of Computer Science National Tsing Hua University Hsinchu 30013 Taiwan

ISBN: (纸本)0769525091

The low-cost and availability of network of workstations have made them attractive solution for high performance computing. Striking progress of network technology is enabling high-performance global computing, with the utilization of cluster and grid technologies, in which computational and data resources in a local or wide area network are transparently employed to solve large-scale problems. In this paper, we present implementation and design rationale of Visuel* toolkit for performance measurement and analysis of parallel applications in cluster and grid environments. Most of performance visualization tools available today for high-performance platforms show solely system performance data (e.g., CPU load, memory usage, network bandwidth, server average load), and thus, being suitable for visualization of computing platform system activities. The Visuel toolkit is web-based interface designed to show performance, activities of all computing nodes of a cluster or grid computing platform involved in the execution of a parallel application, such as CPU load level and memory usage of each computing node. In addition, this toolkit is able to display comparative performance data visualizations generated from a number of executions of an application under investigation, analyzing the performance of different implementations. Evaluations using this toolkit show that it outperforms in easing the process of investigation and implementation of parallel applications, in effective way. © 2005 IEEE.

关键词： Computer workstations

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Location-Aware Multi-user Resource Allocation in distributed Clouds

Location-Aware Multi-user Resource Allocation in Distributed...

引用

10th Annual Conference of Advanced Computer Architecture, ACA 2014

作者： Li, Jiaxin Li, Dongsheng Zheng, Jing Quan, Yong National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China Information Center of Logistics Department Beijing China School of Computer Science National University of Defense Technology Changsha China

ISBN: (纸本)9783662444900

Resource allocation for multi-user across multiple data centers is an important problem in cloud computing environments. Many geographically-distributed users may request virtualized resources simultaneously. And the distances from users to allocated resources have much impact on the quality of service (QoS) in multiple data centers environment. Most existing methods do not take all these factors into account when allocating resources. They usually result in poor runtime performance of users' virtual computing environment and the remarkable difference of users' QoS. In this paper, we propose RAMD, a resource allocation algorithm based on multi-stage decision in multiple data centers. The RAMD algorithm allocate VMs to users, taking into account the correlation and interaction between multiple users, so as to minimize the sum of all users' service distances (i.e. determined by user location and network distance of virtual machines). Experimental results show that the algorithm can effectively deal with the cloud resource allocation for multi-user across multiple data centers. It can improve the runtime performance of users' virtualized resources and reduce the difference of QoS. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Resource allocation

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Short-Term Rainfall Estimation by Machine Learning Methods

Short-Term Rainfall Estimation by Machine Learning Methods

引用

IEEE International Scientific Conference on Informatics

作者： Peter Krammer Marcel Kvassay Ondrej Habala Ladislav Hluchý Department of Parallel and Distributed Information Processing Institute of Informatics Slovak Academy of Sciences Bratislava Slovakia

ISBN: (数字)9781728131801

ISBN: (纸本)9781728131818

Modeling stochastic systems is a real challenge in many areas. Even the meteorology domain is not an exception; the modeling of precipitation activity is markedly stochastic and is influenced by a number of related physical variables (temperature, pressure, humidity, wind). Accurate precipitation estimation is thus highly non-trivial. Today's technical capability, automated data measuring (whether using Radar or automatic meteorological stations), as well as subsequent large-scale data processing and regression model training, allow the meteorological estimations and predictions with increasing accuracy. This paper demonstrates selected uses of artificial neural networks in the field of meteorology, as well as solving problems with pre-processing and integrating time-spatial meteorological data.

关键词： Temperature measurement Atmospheric modeling Meteorology Meteorological radar Sea measurements Reflectivity

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