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

共 1599 条记录，以下是291-300 订阅

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the 10th international conference on Computer Engineering and Networks 1st ed. 2021

The 10th International Conference on Computer Engineering an...

引用

丛书名： Advances in Intelligent Systems and computing

2021年

作者： Qi Liu Xiaodong Liu Tao Shen Xuesong Qiu

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Workload Distribution on Heterogeneous Platforms

Workload Distribution on Heterogeneous Platforms

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10th IEEE international conference on Computer, Information and Telecommunication Systems (IEEE CITS)

作者： Alasmar, Mahmoud Bazlamacci, Cuneyt F. Middle East Tech Univ Elect & Elect Engn Dept Ankara Turkey Izmir Inst Technol Comp Engn Dept Izmir Turkey

ISBN: (纸本)9781665449137

this paper targets the problem of finding an efficient distribution of a computational task on a heterogeneous computing platform. the heterogeneity of the processing elements arise due to differences in computation speed and memory capacity of the processors. We first consider using a discrete functional performance model that integrates processing speed and capacity of processing elements and then develop a mathematical model and propose a heuristic mapping algorithm for distributing a given total workload of size N on p processing elements such that the total computation time is minimized Computational results show that the proposed method provides a significant improvement in reducing the computation time in comparison to equal distribution approach.

关键词： Heterogeneous computing Platform High Performance computing Workload Distribution Task assignment Functional Performance Model

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Safety Application Platform of Energy Production Surveillance Based on Data Flow 10th

Safety Application Platform of Energy Production Surveillanc...

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10th international conference on Big Data (BigData) Held as Part of the 19th Services conference Federation (SCF)

作者： Fan, Xiaohu Gong, Mingmin Pang, Xuejiao Feng, Hao Wuhan Coll Dept Informat Engn Wuhan 430212 Peoples R China Wuhan Opt Valley Info & Tech Co Ltd Wuhan Peoples R China

ISBN: (纸本)9783030962821;9783030962814

With the development of urbanization, the social demand for energy is increasing. the safety production monitoring of electric power has always been an important issue related to the national economy and people's livelihood. thanks to deep learning technology, a large number of monitoring and computer vision analysis algorithms have begun to popularize, but only in some simple scenes, or only after investigation and evidence collection. Due to the lack of training samples, the traditional machine learning method cannot be used to train the generative model in hazard situations. Besides, it is a pressure and challenge to the calculation capacity, bandwidth and storage of the system. this paper proposes a platform level solution based on data flow, which can use a large number of cost-effective general-purpose devices to form a cluster, and adjust the task load of each computing unit through software level resource scheduling. the equipment adopts 2U general specification, which can provide better heat dissipation and improve the cooling efficiency of the cluster. At present, the system has been deployed in several pilot projects of the State Grid. It uses LSTM algorithm to establish the contour with normal data training, and uses the deviation of 12.5% as the threshold to identify the abnormal scene. It can accurately identify the obvious suspected abnormal behavior with 98.6% and push it to the operation and maintenance personnel for secondary confirmation.

关键词： Data flow Massive video data LSTM High performance computing

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Robust Zero Watermarking Algorithm for Medical Volume Data Based on LBP 10th

Robust Zero Watermarking Algorithm for Medical Volume Data B...

引用

10th KES international conference on Innovation in Medicine and Healthcare, KES-InMed 2022

作者： Liu, Wenyi Li, Jingbing Liu, Jing Ma, Jixin School of Information and Communication Engineering Hainan University Haikou570228 China Research Center for Healthcare Data Science Zhejiang Lab Hangzhou310058 China School of Computing and Mathematical Sciences University of Greenwich LondonSE10 9LS United Kingdom

ISBN: (纸本)9789811934391

With the gradual rise of telemedicine, a large number of images will be transmitted on the network during network consultation, which may cause privacy disclosure. How to more effectively ensure the information security of patients and the copyright of medical images has attracted great attention of scholars in relevant fields. this paper proposed a robust watermarking method for medical volume data based on local binary pattern (LBP) transformation. Firstly, taking the Medical Volume Data as the research object, the low frequency feature vector of the Medical Volume Data is extracted by combining local binary mode transform and discrete cosine transform. then hash perception was performed. Finally, we use zero watermark technology to embed the hash sequence and chaotic technology to encrypt watermark. Experimental prove that the proposed algorithm has strong anti-attack abilities. © 2022, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Local binary pattern

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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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An assessment of various clustering techniques for VANET 10

An assessment of various clustering techniques for VANET

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

作者： Barve, Atul Patheja, Pushpinder Singh School of Computing Sc. & Engg. VIT Bhopal University Madhya Pradesh Bhopal India

ISBN: (纸本)9780738105239

Vehicular Adhoc Network (VANET) is a technology where various vehicles on the road use Wireless Adhoc network technique for making communication among them for better driving environment and laser probability of roadside accidents. the vehicles are considered as wireless mobile nodes. these mobile nodes will form a network using various network topologies. these vehicles will communicate with each other using wireless communication technology. Intelligent Transportation System (ITS) is an application which plans to offer inventive types of assistance to traffic the *** wireless nodes are allowed to communicate in about short range so vehicle networks are further divided in the clusters to make communication among neighbors’ vehicles within the cluster. the formation of clusters is based on various parameters like speed, direction, density, velocity etc. these clusters are variable in nature, so maintaining a cluster head in a cluster is a very tedious task. this paper surveys various clustering adopted in the VANET with their possible benefits and drawbacks. © 2021 IEEE.

关键词： Vehicles

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A Facial Expression recognition System for Smart Learning Based on YOLO and Vision Transformer 2021

A Facial Expression Recognition System for Smart Learning Ba...

引用

7th international conference on computing and Artificial Intelligence, ICCAI 2021

作者： Ling, Xufeng Liang, Jingxin Wang, Dong Yang, Jie Shanghai Normal University Tianhua College Ai School No. 1661 North Sheng Xin Road China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University China

ISBN: (纸本)9781450389501

this paper proposes a facial expression recognition system for smart learning on classroom. Firstly, YOLO is used to extract face images of multiple students from high-resolution video;secondly, face images are preprocessed, then a self-attention based model named Vision Transformer (ViT) is used to recognize facial expressions;finally, the classified facial expression is used to assist teacher to analyze students' learning status, so as to provide suggestions for improving teaching effect. © 2021 ACM.

关键词： Students

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Quantum Based Deep Learning Models for pattern recognition 6th

Quantum Based Deep Learning Models for Pattern Recognition

引用

6th international conference on Information, Communication and computing Technology (ICICCT)

作者： Shrivastava, Prakhar Soni, Kapil Kumar Rasool, Akhtar MANIT Dept Comp Sci Engn Bhopal Madhya Pradesh India

ISBN: (纸本)9783030883782;9783030883775

the machine learning model influences the pattern recognition based on extraction of relative patterns, but not enough capable of efficiently processing the data set that needs layered interaction. So, deep learning model takes the advantage of artificial neural network for processing the data in layered abstraction by exploring massive parallelism, although the classical implementations of such model may not be competent due to the processing and storage of large neural networks. Current research explores quantum computation potentials and utilizes its significance for supporting inherent parallelism, as the machine perform exponential operations in single step of execution. the possible classical designs of pattern recognition using deep learning are Hopfield network and Boltzmann machine and their equivalent quantum models can remain effective and overcome the processing limitations of classical model by incorporating Grover's search method and quantum Hebbian learning. the aim of writing this article is to introduce the necessity of deep learning model, an emergence of quantum computations, discussion over requisites of data preprocessing techniques, then to propose the classical equivalent quantum deep learning model along with the algorithms, complexity comparison and speedup analysis followed by conclusive aspects that proves effectiveness of quantum deep learning model and future works.

关键词： Quantum pattern recognition Machine learning Deep learning Grover's search Neural networks Superposition Quantum Hebbian learning

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Analysis of Eye Fixations During Emotion recognition in Talking Faces 9

Analysis of Eye Fixations During Emotion Recognition in Talk...

引用

9th international conference on Affective computing and Intelligent Interaction (ACII)

作者： Cao, Houwei Elliott, Forest New York Inst Technol Dept Comp Sci New York NY 10023 USA Oberlin Coll Dept Comp Sci Oberlin OH 44074 USA

ISBN: (纸本)9781665400190

Research on emotion recognition from cues expressed in facial expression has a long-standing tradition. In this study, we investigate human's visual attention and fixation patterns when identifying six basic emotions on expressive talking faces. Stimuli for the current experiments consisted of 92 video clips of facial expression during talking. the whole experiments were divided into two sessions. the video stimuli in the first session were presented in random order across different face identities, while in the second session the video from the same face identity were be played sequentially. the participants' eye movements were recorded by the Tobii X3-120 screen-based eye-tracking system. We defined a set of area-of-interest (AOI) regions, including 4 AOIs of general face areas and 12 AOIs related to specific Action Units (AUs) involved in the coding of the six basic emotions. the gaze pattern analysis was done by looking at the fixation time on this predetermined set of AOIs. Based on the ANOVA analysis, we did not find significant differences in mean fixation time on any AOI for discriminating the six basic emotions, but a subset of significant AOIs was found when we sectioned the six basic emotions into positive, negative, and neutral. Next, we propose to develop a novel emotion perception classifier which can automatically classify an observer's emotion perception based on her gaze patterns and fixation sequence when identifying the basic emotions on expressive talking faces. the fixation time on the 16 predetermined AOIs were used as features to train support vector machine (SVM) models. the proposed models achieved the overall classification accuracy of 84.1% on recognizing 3-way emotions of negative, positive and neutral, suggesting that the proposed eye gaze patterns - the fixation time on 16 predetermined AOIs, are very promising for automatic classification of the perceived emotions. Finally, we divided the data into different gender and race groups, and

关键词： eye fixation emotional face gaze pattern emotion recognition gaze diversity

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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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