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

共 1677 条记录，以下是431-440 订阅

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17th IFIP WG 12.5 international conference on Artificial Intelligence Applications and Innovations, AIAI 2021, 6th Workshop on 5G-Putting Intelligence to the Network Edge, 5G-PINE 2021, Artificial Intelligence in Biomedical Engineering and Informatics Workshop, AI-BIO 2021, Workshop on Defense Applications of AI, DAAI 2021, Distributed AI for Resource-Constrained Platforms Workshop, DARE 2021, Energy Efficiency and Artificial Intelligence Workshop, EEAI 2021, and 10th Mining Humanistic Data Workshop, MHDW 2021

17th IFIP WG 12.5 International Conference on Artificial Int...

引用

17th IFIP WG 12.5 international conference on Artificial Intelligence Applications and Innovations, AIAI 2021, 6th Workshop on 5G-Putting Intelligence to the Network Edge, 5G-PINE 2021, Artificial Intelligence in Biomedical Engineering and Informatics Workshop, AI-BIO 2021, Workshop on Defense Applications of AI, DAAI 2021, Distributed AI for Resource-Constrained Platforms Workshop, DARE 2021, Energy Efficiency and Artificial Intelligence Workshop, EEAI 2021, and 10th Mining Humanistic Data Workshop, MHDW 2021

ISBN: (纸本)9783030791568

the proceedings contain 40 papers. the special focus in this conference is on Artificial Intelligence Applications and Innovations. the topics include: Top Challenges in 5G Densification;TYPHON: Hybrid Data Lakes for Real-Time Big Data Analytics – An Evaluation Framework in the Telecom Industry;V2X Communications for the Support of GLOSA and Intelligent Intersection Applications;a Machine Learning Approach for recognition of Elders’ Activities Using Passive Sensors;analyzing Collective Knowledge Towards Public Health Policy Making;evaluating Mental Patients Utilizing Video Analysis of Facial Expressions;an Inception-Based Architecture for Haemodialysis Time Series Classification;a Lipschitz - Shapley Explainable Defense Methodology Against Adversarial Attacks;A Multimodal AI-Leveraged Counter-UAV Framework for Diverse Environments;5G-VICTORI: Future Railway Communications Requirements Driving 5G Deployments in Railways;cyber Attack Detection and Trust Management Toolkit for Defence-Related Microgrids;On the Potential of SDN Enabled Network Deployment in Tactical Environments;a First Sensitivity Study of Multi-object Multi-camera Tracking Performance;An Initial Analysis of the Shortcomings of Conventional AI and the Benefits of Distributed AI Approaches in Industrial Use Cases;distributed Data Compression for Edge Devices;PFilter: Privacy-Aware and Secure Data Filtering at the Edge for Distributed Edge Analytics;Towards a Distributed Learning Architecture for Securing ISP Home Customers;a Recommendation Specific Human Activity recognition Dataset with Mobile Device’s Sensor Data;Explainable Needn’t Be (Much) Less Accurate: Evaluating an Explainable AI Dashboard for Energy Forecasting;improving Energy Efficiency in Tertiary Buildings through User-Driven Recommendations Delivered on Optimal Micro-moments;5G-VICTORI: Optimizing Media Streaming in Mobile Environments Using mmWave, NBMP and 5G Edge computing.

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the JinYue Database for Huqin Music Emotion, Scene and Imagery recognition 4

The JinYue Database for Huqin Music Emotion, Scene and Image...

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IEEE 4th international conference on Multimedia Information Processing and Retrieval (IEEE MIPR)

作者： Zhang, Kejun Wu, Xinda Tang, Ruiyuan Huang, Qiaoqiao Yang, Changyuan Zhang, Hui Zhejiang Univ Lab CAD CG Hangzhou Peoples R China Int User Experience Business Unit Hangzhou Peoples R China

ISBN: (纸本)9781665418652

Traditional Chinese music is a great treasure for China and the rest of the world, which is accompanied by variant traditional musical instruments and featured with distinct melodies within different dynasties. Developing an efficient music retrieval system for traditional Chinese music requires numerous such music data with rich and accurate annotations. However, existing databases usually consider popular and contemporary music, basic taxonomy, and a single task. In this work, we introduce the JinYue database of more than 1000 pieces of music played by variants of huqin (huqin music) spanning the age range of the 20th century to date. the database includes over 10,000 annotations of huqin music in terms of discrete emotion, scene, and imagery labels. We provide extensive benchmarks of multiclass classification results for emotion, scene, and imagery along with the database. Furthermore, due to the copyright, we develop a JinYue Music Exploring System to provide the information of over 1,000 pieces of music played by huqin, including huqin music metadata, audio features, and annotations. We will continuously collect more music by Chinese musical instruments categories to enrich the JinYue database. this database aims to push forward the research in affective computing, music information retrieval, and beyond.

关键词： traditional Chinese instrumental music database affective computing music emotion recognition huqin music

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recognition of the Cognitive State in the Visual Search Task

Recognition of the Cognitive State in the Visual Search Task

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10th international conference on Applied Human Factors and Ergonomics (AHFE) / AHFE international conference on Neuroergonomics and Cognitive Engineering / AHFE international conference on Industrial Cognitive Ergonomics and Engineering Psychology

作者： Zhang, Shuomo Lu, Yanyu Fu, Shan Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai Peoples R China

ISBN: (纸本)9783030204730;9783030204723

Electroencephalogram (EEG) is a research subject that has been studied constantly. By the analysis of EEG signals, the mental state of the humans can be detected, so it would contribute to the design of human-machine interaction (HMI) systems. In this paper, we intend to study the cognitive state using EEG signals when the subject is performing a visual search task. We tried to obtain the different patterns of the EEG signals when the subject is performing differently in the task. Several pattern recognition algorithms on the signal are conducted to find the principal features in the EEG signals. We can see that the features of EEG signals can present the differences between cognitive states and this result will be beneficial to the recognition of the cognitive state of the operators in the complex systems.

关键词： EEG Signal processing Cognitive state pattern recognition

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A Fast and Robust Embedded Optical Flow Unit on Motion Estimation 2021

A Fast and Robust Embedded Optical Flow Unit on Motion Estim...

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10th international conference on Software and Computer Applications, ICSCA 2021

作者： Rehman, Mubashara Ming Own, Chung Li, Ziqi College of Intelligence and Computing Tianjin University China

ISBN: (纸本)9781450388825

In the last few decades, deep learning is already being widely used to yield excellent performance, automate processes, pattern detection and natural language processing. Among different types of deep neural networks, convolutional neural network has been most extensively studied. In this study, the authors have introduced a network architecture named Fast Unit of Optical Flow (FUOF), which enables the network to estimate optical flow through a fast and robust approach. Our proposed method, FUOF based on the updating of FlowNetC, which includes a layer that correlates feature vectors at different image locations. We also introduced the Extended Sobel method to extract the spatial information to optimize further computation time. Moreover, to fuse the spatial and temporal information flexibly and comprehensively, two different fuse networks are defined as FUOF-Sum and FUOF-Concat in our study. the fuse mode's main difference is on the summarizing of each channel for concatenating of channels for the feature extraction this simple yet powerful idea validated by the experiments with MPI Sintel and Flying Chairs datasets. According to our results, the network with FUOF can achieve a competitive efficiency on the accuracy of standard error measure, convergence speed, and robustness for optical flow estimation. © 2021 ACM.

关键词： Motion estimation

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Towards a Proactive System of DDoS Attacks Detection in the Cloud 12th

Towards a Proactive System of DDoS Attacks Detection in the ...

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12th international conference on Soft computing and pattern recognition, SoCPaR 2020 and 16th international conference on Information Assurance and Security, IAS 2020

作者： Ouhssini, Mohamed Afdel, Karim Agherrabi, Elhafed LabSIV Department of Computer Science Faculty of Science Ibn Zohr University Agadir Morocco LabIRF-SIC Department of Mathematics Faculty of Science Ibn Zohr University Agadir Morocco

ISBN: (纸本)9783030736880

Nowadays, cloud computing becoming a vital technology for organization and users by providing services through the internet. Flexibility, Efficiency, high scalability, and cost effective are the main advantages of cloud computing. However, cloud computing still suffers against attacks that threat its availability, especially DDoS attacks. this type of attack makes service unavailable by sending a huge number of flows generated by different distributed devices. High false positive rate, high time detection and high computing cost are the main challenges of exiting system of attack detection in the cloud. In this paper, we present new approach to detect DDoS attack in the cloud based on time series analysis and machine learning techniques. Statistical methods and deep learning are used to forecast the number of normal flows in the next minute, if the number of received flows is far exceeded the forecasted number, a preprocessing process is trigged followed by classifier to differ between DDoS attack and normal flows. Our system is evaluated by using public dataset CIDDS-001 and satisfactory results obtained an accuracy of an accuracy of 100%, a f1-score of 99.96% and a time detection of 0.29 s. © 2021, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cloud computing

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Principles and characteristics of quantum computing 10

Principles and characteristics of quantum computing

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202 10th international conference on Engineering Mathematics and Physics, ICEMP 2021

作者： Liu, Dianhao College of Nuclear Equipment and Nuclear Engineering Yantai University Yantai264005 China

With the rapid development of science and technology, people tend to have a higher demand for computing. Classical computers can no longer meet part of the computing needs, so quantum information systems have gained more and more attention. Quantum computers have good parallelism, fast information processing speed, large amount of information storage, and performance in many fields far surpasses classical computers. In this article, the author introduces coherent superposition and part of quantum gates and quantum algorithms meanwhile compares classical computers with quantum computers in many aspects. the advantages and disadvantages of quantum computers in principle are also drawn out. Finally, the author proposes future prospects for quantum computers prediction. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Quantum optics

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A Framework for Comparative Evaluation of High-Performance Virtualized Networking Mechanisms 1

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10th international conference on Cloud computing and Services Science (CLOSER)

作者： Ara, Gabriele Lai, Leonardo Cucinotta, Tommaso Abeni, Luca Vitucci, Carlo Scuola Super Sant Anna Pisa Italy Ericsson Stockholm Sweden

ISBN: (数字)9783030723699

ISBN: (纸本)9783030723682;9783030723699

this paper presents an extension to a software framework designed to evaluate the efficiency of different software and hardware-accelerated virtual switches, each commonly adopted on Linux to provide virtual network connectivity to containers in high-performance scenarios, like in Network Function Virtualization (NFV). We present results from the use of our tools, showing the performance of multiple high-performance networking frameworks on a specific platform, comparing the collected data for various key metrics, namely throughput, latency and scalability, with respect to the required computational power.

关键词： Kernel bypass DPDK Netmap NFV Containers Cloud computing

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Handwritten mathematical expression recognition with self-attention 4

Handwritten mathematical expression recognition with self-at...

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4th international conference on Algorithms, computing and Artificial Intelligence, ACAI 2021

作者： Chi, Xueke Wang, Da-Han Wu, Yuefeng Wu, Yun Fujian Key Laboratory of Pattern Recognition and Image Understanding Xiamen361024 China School of Computer and Information Engineering Xiamen University of Technology Xiamen361024 China

ISBN: (纸本)9781450385053

Attention-based encoder-decoder models have made great success on handwritten mathematical expression recognition in recent years. However, this kind of method has the problem of attention drift, because under the local attention mechanism based on RNN, the high similarity between coding features can cause attention confusion. To settle this problem, we propose an encoder-decoder model with self-attention, which captures the global information of the feature map and fuses the local information of the CNN as complementary features. Experiments are conducted on the CROHME2014 and CROHME 2016 competition datasets. the experimental results show that, when only using the official training dataset, the proposed method achieves recognition accuracies of 51.98% and 50.74% on the CROHME2014 and CROHME2016 competition datasets, respectively, which outperforms the other methods significantly. the improvements demonstrate the effectiveness of the self-attention module. © 2021 ACM.

关键词： Signal encoding

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Comparative Analysis of the 1stand 2ndWave of COVID-19 and Visualizing the Increasing and Decreasing of COVID-19 10

Comparative Analysis of the 1stand 2ndWave of COVID-19 and V...

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

作者： Gupta, Saloni Rastogi, Deependra Chauhan, Kartavya Sharma, Shivani Galgotias University School of Computing Science and Engineering Greater Noida India

ISBN: (纸本)9781665439701

the COVID-19 epidemic spread quickly across nations and country to country counter with lockdowns, about 1.6 billion students remain at home worldwide. Under these situations, and in order to keep student positive on current and for coming challenges. Firstly, we are going to do comparative study on 1st and 2nd wave of corona. Secondly, we are making a website that will give a complete detail about the Coronavirus disease and will tell us about the increasing, death and decreasing cases all over India and will show a map on particular state that will be searched and also make a graph on the particular set of data for the particular searched state. In order to make our website more attractive we are going to use CSS, Html and Python language in developing the website. At last, we will come to know briefly about COVID - 19 (Coronavirus) and also about the cases that are increasing and who all have recovered from it. © 2021 IEEE.

关键词： COVID-19

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Fall detection using human skeleton features 11

Fall detection using human skeleton features

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11th international conference of pattern recognition Systems, ICPRS 2021

作者： Ramirez, Heilym Velastin, Sergio A. Fabregas, Ernesto Meza, Ignacio Makris, Dimitrios Farias, Gonzalo Escuela de Ingeniería Eléctrica Pontificia Universidad Católica de Valparaíso Av. Brasil 2147 Valparaíso2362804 Chile School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom Department of Computer Science and Engineering Universidad Carlos III de Madrid Madrid Leganés28911 Spain Departamento de Informática y Automática Universidad Nacional de Educación a Distancia Juan del Rosal 16. Madrid28040 Spain Faculty of Science Engineering and Computing Kingston University LondonSW15 3DW United Kingdom

ISBN: (纸本)9781839534300

Falls are one of the leading causes of death and serious injury in people, especially for the elderly. In addition, falls accidents have a direct financial cost for health systems and, indirectly, for the productivity of society. Among the most important problems in fall detection systems is privacy, limitations of operating devices, and the comparison of machine learning techniques for detection. this article presents a fall detection system by means of a k-Nearest Neighbor (KNN) classifier based on camera-vision using pose detection of the human skeleton for the features extraction. the proposed method is evaluated with UP-FALL dataset, surpassing the results of other fall detection systems that use the same database. this method achieves a 98.84% accuracy and an F1-Score of 97.41%. © 2021 Institution of Engineering and Technology. All rights reserved.

关键词： Fall detection

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