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检索条件"任意字段=5th International Conference on Algorithms and Architectures for Parallel Processing"

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18th international conference on algorithms and architectures for parallel processing, ICA3PP 2018

18th International Conference on Algorithms and Architecture...

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18th international conference on algorithms and architectures for parallel processing, ICA3PP 2018

ISBN: (纸本)9783030050535

the proceedings contain 191 papers. the special focus in this conference is on algorithms and architectures for parallel processing. the topics include: Incentivizing multimedia data acquisition for machine learning system;Toward performance prediction for multi-BSP programs in ML;exploiting the table of energy and power leverages;a semantic web based intelligent IoT model;Accelerating CNNs using optimized scheduling strategy;data analysis of blended learning in python programming;APs deployment optimization for indoor fingerprint positioning with adaptive particle swarm algorithm;deployment optimization of indoor positioning signal sources with fireworks algorithm;a study of sleep stages threshold based on multiscale fuzzy entropy;qoS-driven service matching algorithm based on user requirements;Blind estimation algorithm over fast-fading multipath OFDM channels;facial shape and expression transfer via non-rigid image deformation;p-schedule: Erasure coding schedule strategy in big data storage system;Answer aggregation of crowdsourcing employing an improved EM-based approach;a parallel fast fourier transform algorithm for large-scale signal data using apache spark in cloud;task offloading in edge-clouds with budget constraint;motion trajectory sequence-based map matching assisted indoor autonomous mobile robot positioning;towards the independent spanning trees in the line graphs of interconnection networks;POEM: Pricing longer for edge computing in the device cloud;mobility analysis and response for software-defined internet of things;Research on overload classification method for bus images based on image processing and SVM;DStore: A distributed cloud storage system based on smart contracts and blockchain;towards an efficient and real-time scheduling platform for mobile charging vehicles;Streaming ETL in polystore era.

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Elevated Learning based Secured Phishing Website Identification Methodology using Artificial Intelligence Assistance

Elevated Learning based Secured Phishing Website Identificat...

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Electronics and Sustainable Communication Systems (ICESC), 2020 international conference on

作者： G. Ramkumar Department of ECE Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Saveetha University Chennai

ISBN: (数字)9798350379945

ISBN: (纸本)9798350379952

Phishing attacks pose a huge threat for online security and therefore need advanced detecting techniques in order to mitigate the damages it causes. this paper introduces a sophisticated model for the detection of phishing websites, named the Blended ResNet-EfficientNet Model (BREM), which unifies the advantages of the ResNet and EfficientNet architectures. To address this challenge, BREM uses the rich hierarchical pattern recognition ability of ResNet-50 and the practical feature extraction capability of EfficientNet-B3 to achieve classification performance in phishing detection. On overall assessment BREM outperforms both traditional machine learning models and standalone deep learning model with an accuracy of 96%, precision at 94%, recall of 95% and FI score of 94.5%. these same authors validate the high specificity (97 %), negative predictive value (95 %) and Matthews correlation coefficient of 0.92 further underlining the robustness and reliability of BREM. this approach does not only improve the accuracy of detection, but also provides much better security against phishing campaigns. In the near future research directions such as real-time deployment, more experiments on different feature sets, adversarial robustness, transfer learning from heterogeneous datasets, model learning models and pattern recognition. they are able to draw from an immense amount of data and address minor deviances, which allows AI's better discrimination of real versus false websites, therefore increasing user cyber protections and preventable breaches [3] [4]. At the heart of securing phishing websites identification is making use of powerful AI capabilities to scan and recognize phishing convincingly. this AI utilizes different methods - natural language processing (NLP), image recognition and behavioral analysis - to keep an eye on things happening to web content and its design. Behavior analysis tracks user-interactions and web behavior to detect for abnormal operations, which co

关键词： Accuracy Phishing Scalability Transfer learning Robustness Natural language processing Real-time systems Pattern recognition Security Protection

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18th international conference on algorithms and architectures for parallel processing, ICA3PP 2018

18th International Conference on Algorithms and Architecture...

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18th international conference on algorithms and architectures for parallel processing, ICA3PP 2018

ISBN: (纸本)9783030050566

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parallelization of the Array Method Using OpenMP 20th

Parallelization of the Array Method Using OpenMP

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20th Mexican international conference on Artificial Intelligence (MICAI)

作者： Velarde Martinez, Apolinar Inst Tecnol El Llano Aguascalientes Carretera Aguascalientes San Luis PotosiKm 18 Aguascalientes Aguascalientes Mexico

ISBN: (纸本)9783030898205;9783030898199

Shared memory programming and distributed memory programming, are the most prominent ways of parallelize applications requiring high processing times and large amounts of storage in High Performance Computing (HPC) systems;parallel applications can be represented by parallel Task Graphs (PTG) using Directed Acyclic Graphs (DAGs). the scheduling of PTGs in HPCS is considered a NP-Complete combinatorial problem that requires large amounts of storage and long processing times. Heuristic methods and sequential programming languages have been proposed to address this problem. In the open access paper: Scheduling in Heterogeneous Distributed Computing Systems Based on Internal Structure of parallel Tasks Graphs with Meta-Heuristics, the Array Method is presented, this method optimizes the use of processing Elements (PE) in a HPCS and improves response times in scheduling and mapping resource with the use of the Univariate Marginal Distribution Algorithm (UMDA);Array Method uses the internal characteristics of PTGs to make task scheduling;this method was programmed in the C language in sequential form, analyzed and tested with the use of algorithms for the generation of synthetic workloads and DAGs of real applications. Considering the great benefits of parallel software, this research work presents the Array Method using parallel programming with OpenMP. the results of the experiments show an acceleration in the response times of parallel programming compared to sequential programming when evaluating three metrics: waiting time, makespan and quality of assignments.

关键词： parallel Task Graphs (PTG) High Performance Computing (HPC) Systems Scheduling tasks Univariate Marginal Distribution Algorithm (UMDA) Array method

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18th international conference on algorithms and architectures for parallel processing, ICA3PP 2018

18th International Conference on Algorithms and Architecture...

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18th international conference on algorithms and architectures for parallel processing, ICA3PP 2018

ISBN: (纸本)9783030050504

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Bengali Place Name Recognition - Comparative Analysis Using Different CNN architectures 5th

Bengali Place Name Recognition - Comparative Analysis Using ...

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5th international conference on Computer Vision and Image processing, CVIP 2020

作者： Prasad, Prashant Kumar Banerjee, Pamela Chanda, Sukalpa Pal, Umapada RCC Institute of Information Technology Kolkata India Department of Information Technology Østfold University College Halden Norway Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9789811610912

Optical Character Recognition (OCR) has been deployed in the past in different application areas such as automatic transcription and indexing of document images, reading aid for the visually impaired persons, postal automation etc. However, the performance in many cases has not been impressive due to the fact that character segmentation is itself an error-prone and difficult operation, which leads to the poor performance of the system due to erroneous segmentation of characters. Hence, for many applications (like document indexing, Postal automation) where full character-wise transcription is not required, word recognition is the preferred method these days. this article investigates recognition of Bengali place names as word images using 5 different traditional architectures. Experiments on word images (of Bengali place names) from 608 classes were conducted. Encouraging results were obtained in all instances. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Image recognition

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7th Latin American High Performance Computing conference, CARLA 2020

7th Latin American High Performance Computing Conference, CA...

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7th Latin American High Performance Computing conference, CARLA 2020

ISBN: (纸本)9783030680343

the proceedings contain 15 papers. the special focus in this conference is on Latin American High Performance Computing. the topics include: Electricity Demand Forecasting Using Computational Intelligence and High Performance Computing;parallel/Distributed Generative Adversarial Neural Networks for Data Augmentation of COVID-19 Training Images;analysis of Regularization in Deep Learning Models on Testbed architectures;computer Application for the Detection of Skin Diseases in Photographic Images Using Convolutional Neural Networks;Neocortex and Bridges-2: A High Performance AI+HPC Ecosystem for Science, Discovery, and Societal Good;Fostering Remote Visualization: Experiences in Two Different HPC Sites;high Performance Computing Simulations of Granular Media in Silos;performance Analysis of Main Public Cloud Big Data Services processing Brazilian Government Data;accelerating Machine Learning algorithms with TensorFlow Using thread Mapping Policies;Methodology for Design and Implementation an Efficient HPC Cluster;estimating the Execution Time of the Coupled Stage in Multiscale Numerical Simulations;Using HPC as a Competitive Advantage in an international Robotics Challenge;a Survey on Privacy-Preserving Machine Learning with Fully Homomorphic Encryption.

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18th international conference on algorithms and architectures for parallel processing, ICA3PP 2018

18th International Conference on Algorithms and Architecture...

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18th international conference on algorithms and architectures for parallel processing, ICA3PP 2018

ISBN: (纸本)9783030050627

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A Study on the Effectiveness of Deep Learning architectures in Style Transfer: A Comparative Analysis of CNN, VGG16, and VGG19 23

A Study on the Effectiveness of Deep Learning Architectures ...

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Proceedings of the 2023 5th international conference on Big-data Service and Intelligent Computation

作者： Zhixiang Wang Mengtong Xie Yi Lin Tong Wu University of Electronic Science and Technology of China China University of Nottingham UK Guangdong Technion-Israel Institute of Technology China The Pennsylvania State University USA

ISBN: (纸本)9798400708923

this study explores the performance differences among different deep learning models, including VGG19, VGG16, and a basic CNN, in the context of image style transfer. Style transfer is an image processing technique aimed at transferring the artistic style of one image onto the content of another. Our research motivation stems from the potential applications of style transfer across various domains and the opportunities for enhancing model performance. through a series of experiments, we assess the performance of these models in terms of the visual quality of generated images, style preservation, feature extraction, and training efficiency. the results demonstrate significant variations in performance across diverse and complex conditions, especially in tasks involving advanced features. VGG19 and VGG16 exhibit exceptional performance, accurately capturing and conveying high-level features, resulting in the generation of synthesized images with artistic value. However, for tasks emphasizing speed and resource efficiency, the basic CNN also exhibits notable advantages. Lastly, we discuss the limitations of the study and provide suggestions for future work to further optimize model performance. In conclusion, the choice of an appropriate deep learning model should be determined by the nature and requirements of the task. this research provides valuable insights into the applications of different models in the field of image style transfer.

关键词： Basic CNN Deep Learning Models Feature Extraction Image processing Loss Function Model Performance Style Transfer VGG16 VGG19

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A Review on Application of Deep Learning in Natural Language processing

A Review on Application of Deep Learning in Natural Language...

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international conference on Contemporary Computing and Informatics (IC3I)

作者： Pravin Ramdas Kshirsagar Dhoma Harshavardhan Reddy Mallika Dhingra Dharmesh Dhabliya Ankur Gupta Department of Artificial Intelligence G H Raisoni College of Engineering Nagpur Maharashtra India Trainee Security Analyst JunoClinic Davman Technology Services Private Limited Mumbai Maharashtra India Department of Mathematics and Statistics Manipal University Jaipur Jaipur Rajasthan India Department of Information Technology Vishwakarma Institute of Information Technology Pune Maharashtra India Department of Computer Science and Engineering Vaish College of Engineering Rohtak Haryana India

Natural Language processing (NLP) is a developing method utilized in building different sorts of Artificial Intelligence (AI) that is available in today’s time. More intellectual applications will tend to be a primary goal for ongoing and upcoming research. the requirement and desire for data-driven strategies for automatic semantic analysis have risen as a result of recent improvements in processing capacity as well as the accessibility of enormous several linguistic records. A boom in the applications throughout the previous several years of deep learning approaches has advanced the area of natural language processing. this review offers a succinct summary of deep learning architectures and techniques as well as a basic introduction to the area. Our goal is to develop a theoretical study of numerous sectors where NLP may have a significant impact and completely alter the situation with its automated approaches. Everyone is interested in investing in it since it is a hot issue. An in-depth investigation of NLP and its field is used to create these applications. Natural language processing (NLP) trends and its constituent parts are covered in the introduction to this article before it discusses applications for NLP, its emergence, and related issues.

关键词： Deep learning Computer science Semantics Linguistics Market research Natural language processing Artificial intelligence

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