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

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Do You See What I See?

Do You See What I See?

引用

IEEE Applied imagery Pattern Recognition (AIPR) Workshop on Sensing for Control and Augmentation

作者： Cerkez, P. S. DCS Corp Lexington Pk MD 20653 USA

ISBN: (纸本)9781479925407

Semagrams are a subset of steganography. When a message is transmitted in a non-textual format, (i.e., in the visual content of an image), it is referred to as a semagram. While semagrams are relatively easy to create (as shown in published papers covering hiding techniques), detecting a hidden message in or embedded as an image-based semagram is a greater magnitude of difficultly than typical digital steganography. US Patents issued based on semagram technology show that this feature has been exploited in the copyright/watermarking world to increase protection. In a semagram, the image is the message and they work well for simple messages and dead drops. Attacks on semagrams are primarily visual examinations of artifacts. In the counter-espionage world, the rule of the thumb is that there is always a message hidden in an image or graphic, it is simply up to the steganalyst to find it. In short, detecting semagrams is a matter of recognizing patterns of patterns that represent a hidden message within an image. This presentation provides a brief summary of the technology underlying semagrams, present a short non-technical discussion of the technology used in the attack on semagrams, followed by a discussion on current work and planned future implementations of the proven semagram detection ANN. It will focus on extending the ANN to other domains (e. g., non-visual spectrums, multi/cross spectrum correlation, scene identification, image classification) and efforts to improve the processing speed and throughput via parallel/distributed methods.

关键词： images imagery (Psychotherapy) Steganography Messages image processing SPEED Spectra Thumb Artificial neural networks Throughput

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Efficient Hardware Calculation of Running Statistics

Efficient Hardware Calculation of Running Statistics

引用

28th International Conference on image and Vision Computing New Zealand (IVCNZ)

作者： Bailey, Donald G. Klaiber, Michael J. Massey Univ Sch Engn & Adv Technol Palmerston North New Zealand Univ Stuttgart Inst Parallel & Distributed Syst Stuttgart Germany

ISBN: (纸本)9781479908837;9781479908820

Calculation of mean, variance and standard deviation are often required for segmentation or feature extraction. In image processing, often an integer approximation is adequate. Conventional methods require division and square root operations, which are expensive to realize in hardware in terms of both the amount of required resources and latency. A new class of iterative algorithms is developed based on integer arithmetic. An implementation of the algorithms as a hardware architecture for a Field-Programmable Gate Array (FPGA) is compared with architectures using the conventional approach, which shows a significantly reduced latency while using less hardware resources.

关键词： Computer hardware hardware resource Field programmable gate arrays hardware architecture Iterative algorithms Feature extraction ARCHITECTURE Integer Latency integer arithmetic segmentation

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DECOMPOSITION BY PARTIAL LINEARIZATION IN MULTIUSER SYSTEMS

DECOMPOSITION BY PARTIAL LINEARIZATION IN MULTIUSER SYSTEMS

引用

IEEE International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Scutari, G. Facchinei, F. Song, P. Palomar, D. P. Pang, J. -S. SUNY Buffalo Dpt Elect Eng Buffalo NY 14260 USA Univ Roma La Sapienza Dept Comp Control & Management Eng Rome Italy Hong Kong Univ Sci & Technol Dept Elect & Comp Engn Hong Kong Hong Kong Peoples R China Univ Illinois Dept Ind & Enterprise Syst Eng Urbana IL 61801 USA

ISBN: (纸本)9781479903566

We propose a decomposition framework for the distributed optimization of general noncoiwex stun-utility functions arising in the design of wireless multi-user interfering systems. Our main contributions are: i) the development of the first provably convergent Jacobi bestresponse algorithm, where all users simultaneously solve a suitably convexified version of the original sum-utility optimization problem;ii) the derivation of a general dynamic pricing mechanism that provides a unified view of existing pricing schemes that are based, instead, on heuristics;and iii) a framework that can be easily particularized to well-known applications, giving rise to practical algorithms that outperform all existing ad-hoc methods proposed for very specific problems. Our framework contains as special cases wellknown gradient algorithms for nonconvex sum-utility problems, and many block-coordinate descents schemes for convex functions.

关键词： Nonconvex social problems parallel & distributed optimization successive convex approximation.

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A multiway model for predicting earthquake ground motion

A multiway model for predicting earthquake ground motion

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14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed Computing, SNPD 2013

作者： Bai, Yang Tezcan, Jale Cheng, Qiang Cheng, Jie Southern Illinois University Carbondale IL 62901 United States University of Hawaii Hilo HI 96720 United States

ISBN: (纸本)9780769550053

This paper develops a novel supervised method for predicting earthquake ground motions in the wavelet domain. The training input is a set of seismological predictors related to seismic source, path and local site conditions, and the training output consists of the weights from a multiway analysis of ground motions. We treat wavelet transforms of acceleration records as images and extract essential patterns from them using tensor decomposition. The decomposition weights of these patterns are then linked to seismological variables using general regression neural network (GRNN). The resulting nonparametric model is then used to predict the wavelet image of an accelerogram for a given set of seismological variables. The predicted image can be transformed back to the time domain using inverse wavelet transform for subsequent processing to match a given design spectrum. Unlike conventional ground motion models, the proposed approach retains the time domain characteristics of ground motions. Pearson's correlation coefficient between the vectorized forms of actual and predicted wavelet images has been used as the similarity metric in assessing the prediction capability of the resulting model. Experimental results demonstrate the ability of the proposed model to predict significant patterns in the seismic energy distribution. © 2013 IEEE.

关键词： Correlation methods

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parallel implementation of a X-ray tomography reconstruction algorithm based on MPI and CUDA 13

Parallel implementation of a X-ray tomography reconstruction...

引用

20th European MPI Users' Group Meeting, EuroMPI 2013

作者： Blas, Javier Garcia Abella, Monica Liria, Ernesto Isaila, Florin Carretero, Jesus Desco, Manuel Computer Architecture and Communication Area University Carlos III Madrid Spain Bioengineering and Aerospace Engineering IiSGM CIBERSAM Madrid Spain

ISBN: (纸本)9788461651337

Most small-animal X-ray computed tomography (CT) scanners are based on cone-beam geometry with a flat-panel detector orbiting in a circular trajectory. image reconstruction in these systems is usually performed by approximate methods based on the algorithm proposed by Feldkamp, Davis and Kress (FDK). Currently there is a strong need to speedup the reconstruction of X-Ray CT data in order to extend its clinical applications. The evolution of the semiconductor detector panels has resulted in an increase of detector elements density, which produces a higher amount of data to process. This work focuses on future high-resolution studies (density up to 4096 pixeles), in which multiple level of parallelism will be needed in the reconstruction. In addition, this paper addresses the future challenges of processing high-resolution images in many-core and distributed architectures. In our evaluation section we demonstrate that our solution is 17% faster than recent related works. Copyright 2013 ACM.

关键词： parallel architectures

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Visualizing parallelism in CS 2

Visualizing Parallelism in CS 2

引用

IEEE International Symposium on parallel and distributed processing Workshops and Phd Forum (IPDPSW)

作者： Sean Massung Cinda Heeren Computer Science Dept University of Illinois at Urbana-Champaign

ISBN: (纸本)9781479913725

This paper describes the incorporation of the IEEE-TCPP Curriculum Initiative into CS 2 at the University of Illinois at Urbana-Champaign. With control over only one course that requires a semi-rigid curriculum, we detail a sequence of three lessons that explore the basics of parallelism in a visual manner. We draw a contrast between standard teaching methods for parallelism and assert that our approach is more engaging and more accessible, particularly to spatial learners. We then present examples of our image-centric course material and discuss its deployment. Lastly, we reflect on the effectiveness of this technique over the past two semesters and consider its direction in the future.

关键词： parallel processing Educational institutions Instruction sets image color analysis Visualization Materials Algorithm design and analysis

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Storm System Database: A Big Data Approach to Moving Object Databases

Storm System Database: A Big Data Approach to Moving Object ...

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4th International Conference on Computing for Geospatial Research and Application (COM.Geo)

作者： Olsen, Brian McKenney, Mark So Illinois Univ Dept Comp Sci Edwardsville IL 62026 USA

ISBN: (纸本)9780769550121

Rainfall data is often collected by measuring the amount of precipitation collected in a physical container at a site. Such methods provide precise data for those sites, but are limited in granularity to the number and placement of collection devices. We use radar images of storm systems that are publicly available and provide rainfall estimates for large regions of the globe, but at the cost of loss of precision. We present a moving object database called Storm DB that stores decibel measurements of rain clouds as moving regions, ie., we store a single rain cloud as a region that changes shape and position over time. Storm DB is a prototype system that answers rain amount queries over a user defined time duration for any point in the continental United States. In other words, a user can ask the database for the amount of rainfall that fell at any point in the US over a specified time window. Although this single query seems straightforward, it is complicated due to the expected size of the dataset: storm clouds are numerous, radar images are available in high resolution, and our system will collect data over a large timeframe;thus, we expect the number and size of moving regions representing storm clouds to be large. To implement our proposed query, we bring together the following concepts: (i) image processing to retrieve storm clouds from radar images, (ii) interpolation mechanisms to construct moving regions with infinite temporal resolution from region snapshots, (iii) transformations to compute exact point in moving polygon queries using 2-dimensional rather than 3-dimensional algorithms, (iv) GPU algorithms for massively parallel computation of the duration that a point lies inside a moving polygon, and (v) map/reduce algorithms to provide scalability. The resulting prototype lays the groundwork for building big data solutions for moving object databases.

关键词： graphics processing units image processing query processing radar imaging visual databases

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distributed and parallel Subarray Beamforming for Near-Field 3D Sonar Imaging

Distributed and Parallel Subarray Beamforming for Near-Field...

引用

International Conference on Computer Science and Network Technology

作者： Yeqiang Han Jiabao Fu Fan Zhou Xiang Tian Yaowu Chen Inst. of Adv. Digital Technol. & Instrum. Zhejiang Univ. Hangzhou China

ISBN: (纸本)9781479905607

The computational load is prohibitive in 3D sonar systems for real-time image generation. In the literature, an efficient frequency beamforming method based on the distributed and parallel subarray (DPS) has been introduced for planar arrays working in the far field. This paper extends the DPS beamforming algorithm to process the signals acquired from a scene in the near field. The alogrithm divides the full populated transducer array into two stage distributed subarrays. It performs parallel beamforming on the first-stage subarrays and applies the approximation for time delays in the near-field beam patterns of the second-stage subarray. The computational efficiency is significantly improved as compared with the traditional methods, while achieving the similar resolutions. In addition, a multi-FPGA signal processor is proposed for implementing the underwater 3-D imaging.

关键词： array signal processing delay systems field programmable gate arrays sonar imaging DPS beamforming algorithm computational load distributed subarray beamforming frequency beamforming method multiFPGA signal processor near-field 3D sonar imaging near-field beam patterns parallel subarray beamforming real-time image generation time delays Array signal processing Arrays Imaging Signal processing algorithms Sonar Three-dimensional displays distributed and parallel subarray beamforming sonar sensor array system sonar signal processing underwater 3D imaging

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Using clusters in undergraduate research: distributed animation rendering, photo processing, and image transcoding

Using clusters in undergraduate research: Distributed animat...

引用

IEEE International Conference on Cluster Computing

作者： Peter Bui Travis Boettcher Nicholas Jaeger Jeffrey Westphal Department of Computer Science University of Wisconsin - Eau Claire Eau Claire Wisconsin

With distributed and parallel computing becoming increasingly important in both industrial and scientific endeavors, it is imperative that students are introduced to the challenges and methods of high performance and high throughput computing. Because these topics are often absent in standard undergraduate computer science curriculums, it is necessary to encourage and support independent research and study involving distributed and parallel computing. In this paper, we present three undergraduate research projects that utilize distributed computing clusters: animation rendering, photo processing, and image transcoding. We describe the challenges faced in each project, examine the solutions developed by the students, and then evaluate the performance and behavior of each system. At the end, we reflect on our experience using distributed clusters in undergraduate research and offer six general guidelines for mentoring and pursing distributed computing research projects with undergraduates. Overall, these projects effectively promote skills in high performance and high throughput computing while enhancing the undergraduate educational experience.

关键词： Computers Animation Browsers Transcoding Reliability

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GPU-Accelerated protein family identification for metagenomics

GPU-Accelerated protein family identification for metagenomi...

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2013 IEEE 37th Annual Computer Software and Applications Conference, COMPSAC 2013

作者： Wu, Changjun Kalyanaraman, Ananth Xerox Innovation Group Xerox Research Center Webster NY United States School of Electrical Engineering and Computer Science Washington State University Pullman WA United States

ISBN: (纸本)9780769549798

The clustering of putative protein/Open Reading Frame (ORF) sequences available from large-scale metagenomics survey projects is a core analytical function that has led to the identification and characterization of novel protein families of environmental microbial communities. The implementation of this function, however, is currently challenged not only by data size but also by data complexity. In this paper, we present a CPU-GPU implementation of a randomized graph clustering heuristic called Shingling, which was originally developed by Gibson et al. Our implementation uses the CPU and GPU for different stages of computation, using GPUs for the most time-consuming steps. Experimental results of a 2M ocean metagenomics data set obtained from the Sorcerer ii Global Ocean Sampling project show that our new implementation is able to achieve a ~7X speedup over our serial implementation without using asynchronous CPU-GPU communication, with the GPU part alone contributing to over ~374X speedup in the accelerated part. Qualitative evaluation of the 2M data set shows that our method is able to improve sensitivity of clustering over existing methods, and is more successful in recruiting more sequences into the clustering without impacting the overall specificity. As a demonstration of a large scale run, we were able to cluster a real world homology graph, containing 11M vertices and 640M edges, and constructed from sequences of an ongoing Pacific Ocean metagenomics survey project, in about 94 minutes. © 2013 IEEE.

关键词： Graphics processing unit

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