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检索条件"任意字段=2021 10th International Conference on Computing and Pattern Recognition"

共 1678 条记录，以下是391-400 订阅

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Performance Comparison Between Support Vector Regression and Long Short - Term Memory for Prediction of Stock Market 10

Performance Comparison Between Support Vector Regression and...

引用

10th international conference on Information and Communication Technology, ICoICT 2022

作者： Sarumpaet, Nova Monica Indwiarti Rohmawati, Aniq Atiqi School of Computing Telkom University Bandung Indonesia

ISBN: (数字)9781665481656

ISBN: (纸本)9781665481656

Stock prediction is one of the exciting solutions in the world of computing. A stock prediction has a vital role in determining the pattern of stock movements over time. A successful price prediction model is profitable for investors to determine the time to buy or sell stocks. In this study, we used Support Vector Regression and Long Short-Term Memory to predict stock price in Nasdaq's dataset. And then, we compare the performance result of both methods to show which method is the most accurate in producing the solutions. the results show that the LSTM model has a better result than the SVR model. the best LSTM model with RMSE value is 192.6, MAE of 144.12, and R-Squared of 0.9941. these results show good performance because they give the smallest error value and the largest R-Squared value. © 2022 IEEE.

关键词： Long short-term memory

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IBD: A Feedback Framework with Deep-learning for IoT-generated Big Data Processing 10

IBD: A Feedback Framework with Deep-learning for IoT-generat...

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10th international conference on System Modeling and Advancement in Research Trends, SMART 2021

作者： Mishra, Vinay Kumar Kumar, Vivek Pandey, Neeraj Kumar Teerthanker Mahaveer University Computer Science and IT Moradabad India Teerthanker Mahaveer University Computer Science and Engineering Moradabad India DIT University School of Computing Dehradun India

ISBN: (纸本)9781665439701

Convolutional Neural Network (CNN) and Recurrent Neural Networks (RNNs)have the ability to find the accurate result in images and text respectively. the best classification results are still awaited due to the high cost of computation and high memory requirements of CNN and RNN. Our work suggests a framework that improves the quality of data at various layers by providing feedback to suggested system. the proposed framework leads to an error free processing system. © 2021 IEEE.

关键词： Recurrent neural networks

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Cloud for Holography and Augmented Reality 10

Cloud for Holography and Augmented Reality

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10th IEEE international conference on Cloud Networking (IEEE CloudNet)

作者： Makris, Antonios Boudi, Abderrahmane Coppola, Massimo Cordeiro, Luis Corsini, Massimiliano Dazzi, Patrizio Andilla, Ferran Diego Gonzalez Rozas, Yago Kamarianakis, Manos Pateraki, Maria Le Pham, thu Protopsaltis, Antonis Raman, Aravindh Romussi, Alessandro Rosa, Luis Spatafora, Elena Taleb, Tarik theodoropoulos, theodoros Tserpes, Konstantinos Zschau, Enrico Herzog, Uwe Harokopio Univ Dept Informat & Telemat Athens Greece Aalto Univ Espoo Finland CNR Pisa Italy OneSource Coimbra Portugal Telefonica Res Barcelona Spain Tecnol Plexus Santiago De C Spain ORamaVR Iraklion Greece Collins Aerosp Cork Ireland HPE Cernusco Sul Naviglio Italy SeeReal Technol Dresden Germany Eurescom Heidelberg Germany

ISBN: (纸本)9781665435383

the paper introduces the CHARITY framework, a novel framework which aspires to leverage the benefits of intelligent, network continuum autonomous orchestration of cloud, edge, and network resources, to create a symbiotic relationship between low and high latency infrastructures. these infrastructures will facilitate the needs of emerging applications such as holographic events, virtual reality training, and mixed reality entertainment. the framework relies on different enablers and technologies related to cloud and edge for offering a suitable environment in order to deliver the promise of ubiquitous computing to the NextGen application clients. the paper discusses the main pillars that support the CHARITY vision, and provide a description of the planned use cases that are planned to demonstrate CHARITY capabilities.

关键词： Cloud computing Edge computing Cloud Services Cloud Infrastructures Network technologies Internet-working

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Local Binary pattern for Binary Object Classification using Coordination Number (CN)∗ and Hu's Moments 9

Local Binary Pattern for Binary Object Classification using ...

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9th IEEE international conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions), ICRITO 2021

作者： Kumar, Ratnesh Mali, Kalyani University of Kalyani Dept. of Computer Science and Engineering West Bengal Nadia India

ISBN: (纸本)9781665417037

Hu's Moment corresponding to the Local Binary pattern (LBP) features vector have been frequently used for binary objects pattern recognition and classification. Hu's Moments are used in a variety of applications due to its geometrically invariant features on object translation, rotation and scaling. In this paper, we have formulated the methodology of the Hu's Moment by using Local Binary patterns. the minimum responding decimal values of the developed model for the Local Binary pattern (LBP) corresponding to the Coordination Number (CN)∗ of each contour point of an object are used to compute Hu's seven moments. We have incorporated the local binary patterns corresponding to the coordination number of object contour points in a modified model for computing similarity between two binary objects. the experimental results conducted on Kimia-99 and MPEG-7 CE datasets demonstrate that our approach shows better results compared to the other existing algorithms. © 2021 IEEE.

关键词： Local binary pattern

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Ophthalmic Medical Image Analysis 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Bhavna Antony Hao Chen Huihui Fang Huazhu Fu Cecilia S. Lee Yalin Zheng

this book constitutes the refereed proceedings of the 10th international Workshop on Ophthalmic Medical Image Analysis, OMIA 2023, held in conjunction with the 26th international conference on Medical Imaging and Comp... 详细信息

ISBN: (数字)9783031440137

ISBN: (纸本)9783031440120

关键词： Image Processing and Computer Vision Artificial Intelligence pattern recognition Computer Systems Organization and Communication Networks

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Water distribution network leakage analysis modeling based on pattern recognition theory

Water distribution network leakage analysis modeling based o...

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10th international conference on computing and Control for the Water Industry

作者： Wu, C. G. Liu, B. C. Yuan, Y. X. Pei, W. Z. Zhao, P. Wang, M. X. Yang, X. D. Harbin Inst Technol Sch Municipal & Environm Engn Harbin 150006 Heilongjiang Peoples R China Anshan Water Supply Gen Co Anshan Liaoning Peoples R China

ISBN: (纸本)9780415548519

Water leakage is now a serious widespread problem in water distribution network (WDN), no matter what pipe material it used, leakage will occur inevitably with time. therefore, the problem of water leakage has become the focus of China's water supply industry. When leakage occurs, the values of the pressure at monitoring points will fluctuate which are relation with leakage degree or location. And it is just like the fingerprints by which software can identify a person. therefore, in this paper, PNN (PNN) is provided for recognizing fluctuations caused by leakage so as to find the leakage locations approximately by the method of Bayesian classifier selector. the model is applied in water supply networks of a city located in Northeast of China, using its actual monitoring data to check the established leakage locating model. then we analyzed the existing problems of model and proposed possible measures for leakage control of water industry.

关键词： pattern recognition

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Improving Performance of Distributed File System through Frequent Block Access pattern-Based Prefetching Algorithm 10

Improving Performance of Distributed File System through Fre...

引用

10th international conference on computing, Communication and Networking Technologies, ICCCNT 2019

作者： Nalajala, Anusha Ragunathan, T. Rajendra, Sri Harsha Tavidisetty Nikhith, Nagamlla Venkata Sai Gopisetty, Rathnamma SRM University Department of CSE Amaravathi AP India Research Scholar at JNIAS Jawaharlal Nehru Technological University Anantapur India

ISBN: (纸本)9781538659069

Prefetching is an important technique used in distributed file system for improving performance. In this paper, we have proposed a novel frequent access pattern-based prefetching algorithm for distributed file system that is implemented in an environment in which multiple types of storage devices such as hard disk, solid state drives and main memory are used. We have also proposed a new placement algorithm for file blocks which move file blocks from one level of memory to other levels of memory by considering the support of the file block access patterns. the combination of frequent access pattern-based prefetching and judicious placement of file blocks in the multiple memory devices in a static manner will reduce the average read access time of the distributed file system. Our simulation results indicate that the proposed algorithm can improve the performance of the distributed file system by considering average read access time and cache hits. For the performance comparison study purpose, we have considered the support-based prefetching algorithm. © 2019 IEEE.

关键词： Virtual storage

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On computing strength of evidence for writer verification

On computing strength of evidence for writer verification

引用

9th international conference on Document Analysis and recognition

作者： Srinivasan, Harisb Kabra, Shrivardhan Huang, Chen Srihari, Sargur SUNY Coll Buffalo CEDAR Dept Comp Sci & Engn Buffalo NY 14222 USA

ISBN: (纸本)9780769528229

the problem of Writer Verification is to make a decision of whether or not two handwritten documents are written by the same person. Providing a strength of evidence for any such decision is an integral part of the writer verification problem. the strength of evidence should incorporate (i) the amount of information compared in each of the two documents (line/half page/full page etc.), (ii) the nature of content present in the document (same/different content), (iii) Features used for comparison and (iv) the error rate of the model used for making the decision. this paper describes the statistical model used for writer verification and also introduces a mathematical formulation to include the above four mentioned parameters, for calculating strength of evidence of same/different writer the statistical model uses Gamma and Gaussian densities to parametrically model the distance space distribution arising from comparing ensemble of pairs of documents. the strength of evidence is mapped to a 9-point qualitative scale for the decision;one that is often used by questioned document examiners. Experiments and results show that with increase in information content from just a single word to a full page of document, the verification accuracy of the model increases.

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A primitive solution to avoid data deduplication in cloud and overcome security threats 10

A primitive solution to avoid data deduplication in cloud an...

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10th IEEE international conference on Communication Systems and Network Technologies, CSNT 2021

作者： Jinila, Y. Bevish Jose, Jithina Vimali, J.S. Ajitha, P. Gowri, S. Sivasangari School of Computing Sathyabama Institute of Science and Technology Chennai India

ISBN: (纸本)9780738105239

In the recent era, a large number of private and corporate users redistribute the data to the cloud providers. In this extremely large amount of data, there exists large amount of copies of repeated duplicate data. the term data duplication is nothing but compressed repeated data. In the existing system, the process of access control is implemented along with data deduplication which can be done on encrypted data as well. In the proposed system, the user will upload the files to the cloud and it will get changed into an encrypted format by the process of hashing which is done by using SHA-256 algorithm. Based on the existence of the file on the cloud server the user may upload or download the same. In addition, DDoS attack detection and implementation of two types of attacks, collusion attack and sybil attack detection for user identity is addressed. Experimental analysis shows that the storage utilization can be maximized and the efficiency and security of cloud server is improved. © 2021 IEEE.

关键词： Cloud storage

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Graph pattern Matching: A Brief Survey of Challenges and Research Directions 3

Graph Pattern Matching: A Brief Survey of Challenges and Res...

引用

3rd international conference on computing for Sustainable Global Development (INDIACom)

作者： Singh, Komal Singh, Vikram Natl Inst Technol Kurukshetra Haryana India

ISBN: (纸本)9789380544199

Due to tremendous intensification of Internet, most of the data is archived and analyzed in graph-structured database. Graph Database is a collection of operational data objects, mapped into huge labeled graph or a set of labeled directed graphs. In recent years, modeling data in graph structure becomes evident and effective for processing in some of the prominent application area like social analytics etc. Graph databases are mapped into data graphs for further computing or processing. Graphs are one of the dominant data modeling tool used in many application areas. Hence, there is a demand for proficient querying techniques on such large data graphs. the user query is mapped into pattern graph, which is constructed by connecting nodes based on links/relationships required by user. the primary objective of graph pattern matching (GPM) is to determine all the candidates matching to a pattern query in a large data graph. this survey paper discusses various graph pattern matching approaches, used by researchers in recent year for query processing. Further, we also highlight the various challenges imposed by modern day computing and possible future research directions in query processing using graph pattern matching.

关键词： Big Data Analytics Graph Data Graph pattern Matching Graph Mining Query Processing

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