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检索条件"机构=Chinese State Key Lab. for Computer Architecture"

共 226 条记录，以下是71-80 订阅

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Quantified Dynamic Metric Temporal Logic for Dynamic Networks of Stochastic Hybrid Automata

Quantified Dynamic Metric Temporal Logic for Dynamic Network...

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International Conference on Application of Concurrency to System Design

作者： Alexandre David Kim G. Larsen Axel Legay Guangyuan Li Danny Bøgsted Poulsen Department of Computer Science Aalborg University State Key Lab. of Computer Science Chinese Academy of Sciences

Multiprocessing systems are capable of running multiple processes concurrently. By now such systems have established themselves as the defacto standard for operating systems. At the core of an operating system is the ability to execute programs and as such there must be a primitive for instantiating new processes - also programs are allowed to die/terminate. Operating systems may allow the executing programs to split (spawn) into more computational threads in order to let programs take advantage of concurrent execution as well. One of the most used modelling languages, Timed Automata, is based on multiple automata interacting thus they easily model the concurrent execution of programs. However, this language assumes a fixed size system in the sense that automata cannot be created at will but must be instantiated when the overall system is created. This is in contrast with the fact that developers are able to create threads when needed. In this paper we present our continued work to incorporate spawning of threads into UPPAAL SMC. Our modelling language, Dynamic Networks of Stochastic Hybrid Automata, is essentially Timed Automata extended with a spawning primitive and a tear-down primitive. The dynamic creation of threads has the side-effect that it is no longer possible to use ordinary logics to specify behaviours of individual threads - because the threads no longer have unique names. In this paper we propose an extension of Metric Temporal Logic with means for quantifying over the dynamically created threads. This makes it possible to zoom in on individual threads and specify requirements to their future behaviour. Furthermore, we present a monitoring procedure for the logic based on rewriting formulas. The presented modelling language and the specification language have been implemented in UPPAAL SMC version 4.1.18.

关键词： Servers Automata Instruction sets Semantics Ports (computers) Delays Stochastic processes

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Parallel optimization of geometric correction algorithm based on CPU-GPU hybrid architecture

Parallel optimization of geometric correction algorithm base...

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International Conference on Vehicle and Mechanical Engineering and Information Technology, VMEIT 2014

作者： Bai, Hong Tao Li, Yu Gang Chen, Li Ying Wang, Yan Ling Beijing Lab of Intelligent Information Technology School of Computer Science Beijing Institute of Technology Beijing 100081 China Beijing Lab of Intelligent Information Technology School of Computer Science Beijing Institute of Technology Beijing China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783038350606

Geometric correction is an essential processing procedure in remote sensing image processing. The algorithms used in geometric correction are time intensive and the size of remote sensing images is very large. Meanwhile, the data to be calculated is in huge size and is accumulating rapidly every day. Hence, the fast processing of geometric correction of remote sensing image becomes an urgent research problem. Through the rapid development of GPU, the current GPU has a great advantage in processing speed and memory bandwidth over CPU. It provides a new way for high performance computing. In this paper, we present three optimization solutions based on CPU-GPU hybrid architecture and the analysis of their performances. Experiments are also given and the results are consistent with the analysis. © (2014) Trans Tech Publications, Switzerland.

关键词： Graphics processing unit

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ADAPTIVE MULTI-TASK LEARNING FOR FINE-GRAINED CATEGORIZATION

ADAPTIVE MULTI-TASK LEARNING FOR FINE-GRAINED CATEGORIZATION

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IEEE International Conference on Image Processing

作者： Gang Sun Yanyun Chen Xuehui Liu Enhua Wu State Key Lab. of Computer Science Inst. of Software Chinese Academy of Sciences

ISBN: (纸本)9781479983407

Multi-task learning has been proposed to improve the generalization performance by learning multiple tasks jointly. One challenge for this learning paradigm is to effectively seek the shared information across multiple tasks. In this paper, we propose a novel multi-task learning method to adaptively share information. Unlike many existing multi-task learning methods which impose strong assumptions on task relatedness, our method captures the relationships among tasks and identifies the disparities of each task simultaneously, thus can flexibly exploit the shared information. Moreover, we apply it to fine-grained categorization problem, which usually suffers from the difficulties of insufficient training data and high inter-class similarity. The experimental results on two widely used datasets show the superiority of our method compared with some state-of-the-art methods.

关键词： Multi-task learning Fine-grained Image categorization Low-rank Learning methods Religious Missions Learning microparticles PARALLEL PROCESSING (computerS) WWOX gene

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A new approach for line recognition in large-size images using hough transform

A new approach for line recognition in large-size images usi...

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16th International Conference on Pattern Recognition, ICPR 2002

作者： Song, Jiqiang Cai, Min Lyu, Michael R. Cai, Shijie Dept. Computer Science and Engineering Chinese University of Hong Kong Hong Kong Hong Kong State Key Lab. of Novel Software Technology Nanjing University Nanjing China

ISBN: (纸本)0769516963

Applications of the Hough Transform (HT) have been limited to small-size images for a long time. For large-size images, peak detection and line verification become much more time-consuming. Many HT-based line detection methods are not able to detect line width. This paper proposes a new approach for detecting line segments using HT, with applicability to large size images, especially for those situations where line width is critical. Our approach applies a boundary recorder to eliminate redundant analyses, and employs an image-analysis-based line-verification method to overcome the difficulty of using a threshold to distinguish short lines from noise. It avoids overlapping lines by removing the pixels of detected line segments, a method which is more robust than only clearing the N×N neighborhood. This approach could be easily extended to improved HT methods that perform global accumulation. Experimental results show that this approach is very time efficient for large-size images. © 2002 IEEE.

关键词： Hough transforms

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Graphics recognition from binary images: One step or two steps

Graphics recognition from binary images: One step or two ste...

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16th International Conference on Pattern Recognition, ICPR 2002

ISBN: (纸本)0769516963

Recognizing graphic objects from binary images is an important task in many real-life applications. Generally, there are two ways to do the graphics recognition: onestep methods and two-step methods. The former recognizes graphic objects from binary images directly, while the latter consists of vectorization and postprocessing. Neither of them is perfect enough to handle all difficulties. This paper first reviews popular graphics recognition methods to understand their advantages and disadvantages. Next, the performance comparison between two classes of methods is made in two important aspects: the time efficiency and the graphics quality, and the experimental results of time-efficiency comparison of 7 popular methods are also reported. Finally, we propose a new hybrid graphics-recognition paradigm to integrate the advantages of both one-step methods and two-step methods and minimize their disadvantages. The proposed paradigm is capable of recognizing straight lines, arcs, circles and curves efficiently, and is helpful for extracting text images in text-graphics touching cases. © 2002 IEEE.

关键词： Binary images

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Graphics recognition from binary images: One step or two steps

Graphics recognition from binary images: One step or two ste...

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Recognizing graphic objects from binary images is an important task in many real-life applications. Generally, there are two ways to do the graphics recognition: one-step methods and two-step methods. The former recognizes graphic objects from binary images directly, while the latter consists of vectorization and postprocessing. Neither of them is perfect enough to handle all difficulties. This paper first reviews popular graphics recognition methods to understand their advantages and disadvantages. Next, the performance comparison between two classes of methods is made in two important aspects: the time efficiency and the graphics quality, and the experimental results of time-efficiency comparison of 7 popular methods are also reported. Finally, we propose a new hybrid graphics-recognition paradigm to integrate the advantages of both one-step methods and two-step methods and minimize their disadvantages. The proposed paradigm is capable of recognizing straight lines, arcs, circles and curves efficiently, and is helpful for extracting text images in text-graphics touching cases. © 2002 IEEE.

关键词： Character recognition

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Data-aware DRAM refresh to squeeze the margin of retention time in hybrid memory cube 14

Data-aware DRAM refresh to squeeze the margin of retention t...

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Proceedings of the 2014 IEEE/ACM International Conference on computer-Aided Design

作者： Yinhe Han Ying Wang Huawei Li Xiaowei Li State Key Lab of Computer Architecture Institute of Computing technology Chinese Academy of Sciences and University of Chinese Academy of Sciences

ISBN: (纸本)9781479962778

With the increase of storage density, DRAM refresh leads to higher overhead of power and bandwidth, particularly in emerging 3D stacked memory design like Hybrid Memory Cube (HMC). To exploit the hardware resources for a smarter solution, we propose a data-aware refresh control scheme, Trial and Error (Trial-n-Error), which leverages the data-pattern dependence characteristics of the cells' retention time to reduce refresh operations. Trial-n-Error is a systematic approach that employs our proposed Synergy Testing to capture the refresh bottleneck of DRAM memory: "weak" cells that have a relatively shorter retention time. By locating the dominant weak cells sensitized by applications, Trial-n-Error can avoid the worst-case refresh setting, and adjust the refresh rate under the control of our self-tuning algorithm. Thus, Trial-n-Error can gradually approach to the possible lower-bound of refresh rate for less energy and memory bandwidth consumption. In experiments of 3D-stacked DRAMs, we successfully eliminate an average of 28% refresh operations and save 21% refresh energy for a set of pre-profiled synthetic data patterns and real benchmarks.

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Sharing model with multi-level feature representations

Sharing model with multi-level feature representations

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作者： Shen, Li Sun, Gang Wang, Shuhui Wu, Enhua Huang, Qingming University of Chinese Academy of Sciences Beijing China State Key Lab. of Computer Science Inst. of Software CAS Beijing China Institute of Computing Technology CAS Beijing100190 China University of Macau China

ISBN: (纸本)9781479957514

Hierarchical classification models have been proposed to achieve high accuracy by transferring effective information across the categories. One important challenge for this paradigm is to design what can be transferred across the categories. In this paper, we propose a novel method to learn a sharing model by taking advantage of multi-level feature representations. Unlike many of the existing methods which learn the sharing model based on identical feature space, multi-level feature detectors enable our model to capture rich visual information in hierarchical category structure. Moreover, hierarchical classifier parameters associated with multi-level feature representations are learned to model the visual correlation in the hierarchy. The experimental results on Caltech-256 dataset and ImageNet subset demonstrate that our method achieves excellent performance compared with some state-of-the-art methods, and shows the advantage of multi-level information transfer. © 2014 IEEE.

关键词： Classification (of information)

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Iterative methods in large field electron microscope tomography

Iterative methods in large field electron microscope tomogra...

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作者： Wan, Xiaohua Phan, Sébastien Lawrence, Albert Zhang, Fa Han, Renmin Liu, Zhiyong Ellisman, Mark Key Lab of Intelligent Information Processing and Advanced Computing Research Lab Institute of Computing Technology Chinese Academy of Sciences Beijing China National Center for Microscopy and Imaging Research University of California San Diego CA 92093 United States Chinese Academy of Sciences Graduate University Beijing China State Key Lab for Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China

Electron tomography (ET) is a powerful technology allowing the three-dimensional (3D) imaging of cellular ultrastructure. These structures are reconstructed from a set of micrographs taken at different sample orientations, the final volume being the solution of a general inverse problem. Two different approaches are used in this context: iterative methods and filtered backprojection. Iterative methods are known to provide high-resolution 3D reconstructions for ET under noisy and incomplete data conditions. However, all previous implementations have been restricted to the straight-line projection models. This is not accurate since electron trajectories in electron microscopes do not follow the straight-line optics assumed for X-rays, and biological samples may warp as a result of being exposed to an electron beam. Compensation for curvilinear trajectories, nonlinear electron optics, and sample warping constitutes a major advance in large-field ET and has made possible resolution down to the molecular level in reconstructions of whole cells. At present these advances are limited to filtered backprojection and have been implemented in the software package TxBR. As the next step in this development, we have modified the ASART method in conjunction with a 3D model. By employing alignment based on general curvilinear trajectories we have been able to show that further improvements can be achieved with iterative methods. We also discuss a unified treatment of the alignment and reconstruction problems within the framework of iterative methods, and the relationship between formulas employed in the update step and cross-validation methods. Copyright © by SIAM. Unauthorized reproduction of this article is prohibited.

关键词： Iterative methods

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RAM-based tone mapping for high dynamic range images

RAM-based tone mapping for high dynamic range images

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2009 IEEE International Conference on Multimedia and Expo, ICME 2009

作者： Jianbing, Shen Hanqiu, Sun Hanli, Zhao Xiaogang, Jin School of Computer Science and Technology Beijing Institute of Technology Beijing 100081 China State Key Lab. of CAD and CG Zhejiang University Hangzhou 310027 China Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong Hong Kong

ISBN: (纸本)9781424442911

In this paper we present a novel tone mapping algorithm for high dynamic range (HDR) images using the retinal adaptation model (RAM). The physiological evidence suggests that the RAM is obtained by measuring intensity-response functions to flashes of light presented under varying adaptation conditions, which leads to a theoretic-sound model that can be flexibly adapted for tone reproduction. The multiplicative-subtractive process of the model can provide high quality tone mapping results for rendering the HDR images. The experimental results demonstrate that our RAM-based tone mapping approach is effective to produce pleasing results on HDR images in a wide range of real-world scenarios. ©2009 IEEE.

关键词： Ophthalmology

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