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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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The Raspberry Pi Education Mine: For Teaching Engineering and Computer Science Students Concepts Like, Computer Clusters, parallel Computing, and distributed Computing

The Raspberry Pi Education Mine: For Teaching Engineering an...

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IEEE International conference on Electro-Information Technology

作者： Heramb Penyala Soad Ibrahim Ayman El Mesalami Old Doinion University Norfolk US

ISBN: (数字)9781728153179

ISBN: (纸本)9781728153186

This paper introduces a simple method of building a prototype cluster of the Raspberry Pi. The Pi cluster is a powerful-low-cost tool for teaching the complex concepts of parallel and distributed computing to undergraduate E&CS students. The performance of the presented Pi cluster is assessed using two different applications of face recognition and image encryption, which are computationally expensive. The paper explains how to compare the performance of the Pi cluster against a traditional high performance traditional cluster. The comparison is designed to help undergraduate students understand the state of the art of the clusters. The paper explains how the Pi clusters fit in the CS curriculum at Old Dominion University. The presented project-based learning is an effective teaching approach that helps the learning of struggling engineering/computer science students from minorities and women groups at ODU.

关键词： Computational modeling Feature extraction Task analysis parallel processing Random access memory Universal Serial Bus distributed computing

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1st International conference on Applied Computing Research to Support Industry: Innovation and Technology, ACRIT 2019

1st International Conference on Applied Computing Research t...

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1st International conference on Applied Computing Research to Support Industry: Innovation and Technology, ACRIT 2019

ISBN: (纸本)9783030387518

The proceedings contain 39 papers. The special focus in this conference is on Applied Computing Research to Support Industry: Innovation and Technology. The topics include: Evaluation of Local Texture Descriptors for Eyebrow-Based Continuous Mobile User Authentication;deep Learning Approach Based Dominant Age Group Based Classification for Social Network;a Novel Detection System for Human Retina Based on Fuzzification Neural Network;a Novel Car-Pooling Optimization Method Using Ant Colony Optimization Based on Network Analysis (Case Study: Tehran);A Trusted MANET Routing Algorithm Based on Fuzzy Logic;Minimum Array Elements and Snapshots for Performance Analysis Based on Direction Of Arrival (DOA) Estimation methods;experimenting Two Machine Learning methods in Classifying River Water Quality;multi View Face Detection in Cattle Using Infrared Thermography;deep Learning for Face Expressions Detection: Enhanced Recurrent Neural Network with Long Short Term Memory;Detection of Copy-Move Forgery in Digital image Based on SIFT Features and Automatic Matching Thresholds;the Application of Artificial Intelligence Technology in Healthcare: A Systematic Review;Gain Scheduling Fuzzy PID Controller for distributed Control Systems;comparative Analysis for Arabic Sentiment Classification;political Articles Categorization Based on Different Naïve Bayes Models;single Runway Aircraft Landing Scheduling Using Simulated Annealing and Exact Timing Method;towards Smart Meter Energy Analysis and Profiling to Support Low Carbon Emissions;prediction of Compressive Strength of High-Performance Concrete: Hybrid Artificial Intelligence Technique;cancellable Face Biometrics Template Using AlexNet;pattern of Diffusion Recognition in a Molecular Communication Model;querying Encrypted Data in Graph Databases;an Effective Protein Multiple Structure Alignment Using parallel Computing.

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Pan-Sharpening Based On parallel Pyramid Convolutional Neural Network

Pan-Sharpening Based On Parallel Pyramid Convolutional Neura...

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IEEE International conference on image processing

作者： Shuai Fang Xiao Wang Jing Zhang Yang Cao Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) Hefei China Department of Automation University of Science and Technology of China Hefei Anhui China

ISBN: (数字)9781728163956

ISBN: (纸本)9781728163963

Existing deep learning-based pan-sharpening methods mainly learn spatial information from a high-resolution (HR) panchromatic (PAN) image for each spectral channel. However, due to the own characteristics of remote sensing image data, the spatial information of PAN image often shows weak correlation with some spectral channel, especially for channels non-overlapped by PAN channel. In this paper, we propose a parallel pyramid network (PPN) for pan-sharpening. First, a three-branch parallel structure is proposed for dealing with PAN image detail, multispectral (MS) images detail and spectral property respectively. Second, pyramid network structure is introduced in two detail branches to solve the problem of weak correlation due to scale difference. Third, the feature level fusion in two detail branches is implemented, which utilizes redundancy between channels to solve detail representation of channels non-overlapped by PAN channel. The qualitative and quantitative experimental results on various data sets demonstrate the superiority of our proposed method over the state-of-the-art methods.

关键词： Spatial resolution Satellites Feature extraction Remote sensing Correlation Distortion

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Robust beamforming against mismatched signal steering vector using ellipsoidal constraints

Robust beamforming against mismatched signal steering vector...

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International conference on parallel distributed and Grid Computing (PDGC)

作者： Diksha Thakur Vikas Baghel Salman Raiu Talluri JUIT Waknaghat Solan India

ISBN: (数字)9781728171326

ISBN: (纸本)9781728171333

In practical array signal processing environment steering vector uncertainties are present which degrade the performance of adaptive beamforming significantly. The steering vector uncertainty occurs primarily due to mismatch in the direction of signal of interest (SOI). This article presents an efficient approach to enhance the performance of adaptive beamforming in the presence of uncertainty in the steering vector of SOI. The proposed method is based on diagonal loading and utilizes the ellipsoidal constraints to reformulate the optimization problem. The output signal to interference noise ratio (SINR) obtained from the proposed beamforming method shows its superiority over the existing robust beamforming methods. Moreover, the proposed beamforming method accurately estimates the power of SOI.

关键词： Interference Signal to noise ratio Array signal processing Uncertainty Loading Covariance matrices Optimization

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Color image Segmentation Using a Fuzzy Inference System 7

Color Image Segmentation Using a Fuzzy Inference System

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7th International conference on Digital Information processing and Communications (ICDIPC)

作者： Tehrani, Ahmad K. N. Macktoobian, Matin Kasaei, Shohreh Sharif Univ Technol Dept Comp Engn Tehran Iran Ecole Polytech Fed Lausanne REACT Grp Lausanne Switzerland

ISBN: (纸本)9781728132969

A novel method is proposed in the scope of image segmentation that solves this problem by breaking it into two main blocks. The first block's functionality is a method to anticipate the color basis of each segment in segmented images. One of the challenges of image segmentation is the inappropriate distribution of colors in the RGB color space. To determine the color of each segment, after mapping the input image onto the HSI color space, the image colors are classified into some clusters by exploiting the K-Means. Then, the list of cluster centers is winnowed down to a short list of colors based on a set of criteria. The second block of the proposed method defines how each pixel of the input image is mapped onto a specified list of segmentation centers (obtained from the previous block). Usage of the Fuzzy Inference System (FIS) is the solution of this paper to allocate a segmentation center to each image pixel. The rules which the FIS utilizes are designed based on the color of each pixel and its nearby neighborhood. To assess the capability of this method, it is applied to the BSDS500 dataset. The structure of proposed method causes the ability of parallel programming which speeds up the run-time. The experimental results illustrate the superiority of the proposed method over the state-of-the-art methods in the image segmentation.

关键词： image Segmentation image Grouping image processing image Analysis Fuzzy Inference System Fuzzy Control System

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Creation of Scenarios for processing Multidimensional Spatial-Temporal Data under Conditions of Uncertainty 22

Creation of Scenarios for Processing Multidimensional Spatia...

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22nd International conference on Soft Computing and Measurements (SCM)

作者： Pisarev, Ivan A. Kotova, Elena E. Pisarev, Andrei S. St Petersburg Electrotech Univ LETI Fac Comp Sci & Technol St Petersburg Russia

ISBN: (纸本)9781728136028

The article discusses a method for constructing scenarios in an adaptive analytical information system for classifying objects and their movement trajectories in real time based on processing information from a large number of spatially separated information sources (sensors) and analyzing dynamic arrays of distributed multidimensional data under conditions of uncertainty. Examples of scenarios that use statistical, interval, fuzzy and stochastic methods for describing uncertainty are given. When developing scenarios for adaptive data processing and analysis, integrated ontologies of the "hydroacoustics" field of knowledge, ontologies of signal processing methods, image processing methods and data analysis methods are used. Creation of scenarios for automated processing of multidimensional spatial-temporal data is carried out in the OntoMASTER network software environment based on semantic Web standards. To support scientific research, a dynamic scripting interface and their testing in a simulator environment is implemented. The learning environment based on the knowledge base is intended for training and retraining of personnel. The results of the work can be applied both in scientific research and in the process of teaching students.

关键词： information processing building scenarios uncertainty conditions probabilistic methods classification

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Joint Optimization for Multi-antenna Relaying Systems Based on Rate Maximization and Antenna Selection Algorithms

Joint Optimization for Multi-antenna Relaying Systems Based ...

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Information Science, parallel and distributed Systems (ISPDS), International conference on

作者： Jin Wang Yu Tian Ying Wang Yi Huang Fen Qin Shanghai Aerospace Electronic Technology Institute Shanghai China

ISBN: (数字)9781728196688

ISBN: (纸本)9781728196695

To improve the transmission rate of multi-antenna relaying systems, a joint optimization algorithm based on rate maximization and antenna selection is proposed. In order to deal with the coupled amplifying-and-forwarding factors and antenna selection sequence, this joint optimization problem is handled by separating the two variables, and its analytical solution is derived according to optimization theorem. Simulation results show that, the proposed algorithm significantly outperforms the conventional methods in terms of system data rate.

关键词： Antennas Relays Optimization Signal to noise ratio Signal processing algorithms Antenna arrays Receiving antennas

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MAD-C: Multi-stage Approximate distributed Cluster-Combining for Obstacle Detection and Localization 24th

MAD-C: Multi-stage Approximate Distributed Cluster-Combining...

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24th International European conference on parallel and distributed Computing (Euro-Par)

作者： Keramatian, Amir Gulisano, Vincenzo Papatriantafilou, Marina Tsigas, Philippas Nikolakopoulos, Yiannis Chalmers Univ Technol Gothenburg Sweden

ISBN: (纸本)9783030105495;9783030105488

Efficient distributed multi-sensor monitoring is a key feature of upcoming digitalized infrastructures. We address the problem of obstacle detection, having as input multiple point clouds, from a set of laser-based distance sensors;the latter generate high-rate data and can rapidly exhaust baseline analysis methods, that gather and cluster all the data. We propose MAD-C, a distributed approximate method: it can build on any appropriate clustering, to process disjoint subsets of the data distributedly;MAD-C then distills each resulting cluster into a data-summary. The summaries, computable in a continuous way, in constant time and space, are combined, in an order-insensitive, concurrent fashion, to produce approximate volumetric representations of the objects. MAD-C leads to (i) communication savings proportional to the number of points, (ii) multiplicative decrease in the dominating component of the processing complexity and, at the same time, (iii) high accuracy (with RandIndex > 0.95), in comparison to its baseline counterpart. We also propose MAD-C-ext, building on the MAD-C's output, by further combining the original data-points, to improve the outcome granularity, with the same asymptotic processing savings as MAD-C.

关键词： Point cloud processing Approximations Fog computing

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image segmentation with local active contours on graphics processing units. 19

Image segmentation with local active contours on graphics pr...

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4th International conference on Smart City Applications (SCA)

作者： Ammar, Abderazzak Bouattane, Omar Youssfi, Mohammed Univ Hassan II Casablanca Lab SSDIA ENSET Mohammadia Morocco

ISBN: (纸本)9781450362894

Active contours model (ACM) is one of the most attractive and popular methods for image segmentation. While the different formulations of the ACM are generally known to be highly computationally demanding, like most of the image processing techniques do, they are however potential candidates for parallelization. The graphics processing units (GPUs) are nowadays increasingly present in all kind of image processing among other research areas. In this paper, our goal was the implementation of a GPU parallelized local based formulation of the active contours model, namely the local binary fitting energy (LBF) algorithm. This algorithm involves a large amount of convolution operation computations. Besides the convolution, many other finite differences based operations involved in the algorithm are readily parallelized. So, almost all the heavy computational work is moved to the GPU side, and the CPU needs only to control the main loop and some intermediate computations. To validate our results, we have been experimenting with medical images of different sizes, and different convolution filtering sizes, by comparing the speedup of the GPU parallel implementation vs the CPU sequential implementation.

关键词： active contours model segmentation parallelization graphics processing units GPU medical images

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Ameliorated Reversibility in RDH-DSC of AES Encrypted images for providing Authentication

Ameliorated Reversibility in RDH-DSC of AES Encrypted Images...

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International conference on Communications and Signal processing

作者： S Karthik D Manimozhi Kumar S Satheesh R Sowmya Arif. A Mohammed B.Thiruvaimalar Nathan V. Karthik working at Sri Krishna College of Engineering and Technology Coimbatore Arunai College of Engineering Tiruvannamalai Rajalakshmi Engineering College Chennai SRM Institute of Science and Technology Ramapuram Chennai

ISBN: (数字)9781728149882

ISBN: (纸本)9781728149899

The proposed paper discusses a technique to retrieve the encrypted images to obtain a better efficiency and embedding rate than other methods. This method infuses the distributed source coding technique to improvise the hiding technique thereby ameliorates the reversibility rate. The flow of the technique goes as follows: Original image which is encrypted with the Advanced Encryption Standard (AES) and is hidden using distributed source coding (DSC) technique. The former process is done by the possessor of the image and the latter is done by the data hider. The receiver can felicitate the image using the embedding key. If the receiver is provided with the encryption and embedding key, he can recover the original image with high security and lossless original data. Thus, this method is an exception compared to the existing technologies.

关键词： Encryption Receivers image coding Streaming media Source coding Electronic mail

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