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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421-430 订阅

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A New Electronic Voting System Based on Elliptic Curve in a Cloud computing Environment 12th

A New Electronic Voting System Based on Elliptic Curve in a ...

引用

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

作者： Semmouni, Meryem Cherkaoui Azougaghe, Ali Nitaj, Abderrahmane Belkasmi, Mostafa ICES Team ENSIAS Mohammed V University in Rabat Rabat Morocco LMNO University of Caen Normandie Caen France

ISBN: (纸本)9783030736880

the process of democratization is developing and promoting due to electronic voting. However, the increase of frauds and the increasing amount of attacks launched by hackers, gave birth to privacy and authentication problems. Cryptography offers multiple solutions to overcome the sensitive data protection issues in e-voting. In this paper, we study the application of elliptic curve cryptography, and use the homomorphic encryption properties to present a new electronic voting system. Our new scheme is based on the homomorphic cryptosystem EC-ELGAMAL [7], and zero knowledge algorithm of Schnorr algorithm for identification and authentication. © 2021, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Personal computing

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Decoupled adaptive convolutional neural networks for the few-shot image classification 4

Decoupled adaptive convolutional neural networks for the few...

引用

4th international conference on pattern recognition and Artificial Intelligence, PRAI 2021

作者： Huang, Wanrong Hu, Yaqing Hu, Shuofeng Liu, Jingde Artificial Intelligence Research Center National Innovation Institute of Defense Technology Beijing China National University of Defense Technology State Key Laboratory of High Performance Computing Changsha China Center for Computational Biology Beijing Institute of Basic Medical Sciences Beijing China College of Joint Operation National Defense University Beijing China

ISBN: (纸本)9781665413220

Deep neural networks have achieved remarkable results in large-scale data domain. However, few-shot image classification is still a difficult and important problem. In this work, we analyze recently proposed deep neural networks of the meta-learning ability enable them to solve few-shot tasks, and try to find out where the ability comes from. Based on the analysis, we conclude a unified meta-learning framework for the few-shot tasks and propose a novel meta-learning network composed of two decoupled convolutional channels. One of them uses a typical convolutional neural network (CNN) to classify the query sample. the other channel is responsible for adaptively generating the parameters of the CNN with the support images. Unlike previous work in which the query and support input always share modules, our approach improves the flexibility and adaptability via decoupling the two channels. We demonstrate that our approach is able to achieve competitive performance with the existing state-of-the-art methods on two common few-shot image classification benchmarks while being substantially simpler and easier to train on. © 2021 IEEE.

关键词： Image classification

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Adversarial Synthesis of Human Pose from Text 1

引用

42nd German conference on pattern recognition, DAGM GCPR 2020 held in parallel with 25th international Symposium on Vision, Modeling, and Visualization, VMV 2020 and 10th Eurographics Workshop on Visual computing for Biology and Medicine, VCBM 2020

作者： Zhang, Yifei Briq, Rania Tanke, Julian Gall, Juergen Computer Vision Group University of Bonn Bonn Germany Bonn-Aachen International Center for Information Technology RWTH-Aachen University Bonn Germany

ISBN: (数字)9783030712785

ISBN: (纸本)9783030712778

this work focuses on synthesizing human poses from human-level text descriptions. We propose a model that is based on a conditional generative adversarial network. It is designed to generate 2D human poses conditioned on human-written text descriptions. the model is trained and evaluated using the COCO dataset, which consists of images capturing complex everyday scenes with various human poses. We show through qualitative and quantitative results that the model is capable of synthesizing plausible poses matching the given text, indicating that it is possible to generate poses that are consistent with the given semantic features, especially for actions with distinctive poses. © 2021, Springer Nature Switzerland AG.

关键词： Generative adversarial networks

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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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Adaptive Central pattern Generator to Control a Modular Lower Limb Rehabilitation Exoskeleton 10

Adaptive Central Pattern Generator to Control a Modular Lowe...

引用

10th international IEEE-EMBS conference on Neural Engineering (NER)

作者： Plaza, Alberto Hernandez, Mar Ramos, Jaime Puyuelo, Gonzalo Garces, Elena Garcia, Elena Marsi Bion Madrid Spain Univ Politecn Madrid Madrid Spain CSIC Ctr Automat & Robot Madrid Spain

ISBN: (纸本)9781728143378

One of the main challenges of current exoskeletons is the adaptation to the patients' walking capabilities. the proposal of a new device made from modular joints actuators offers new ways of adaptability. However, it also requires changes in control techniques. In this contribution, we introduce the use of a central pattern generator (CPG) based on adaptive Hopf oscillators in order to achieve the decentralised architecture for the modular exoskeleton. Hebbian learning algorithm is used to train the Adaptive CPG, using the data collected from a healthy subject's gait to mimic the human walking trajectories on the hip and knee. the analysis shows how the oscillator manages to learn the training signal and proves that once the oscillator has completed the learning process it no longer needs this signal. Furthermore, its modulation properties of amplitude and frequency are demonstrated, turning out to be suitable in the exoskeletons' control. Finally, results show how the algorithm is tested in two different configurations of the modular exoskeleton prototype, confirming its functioning.

关键词： Neural Networks Central pattern Generator Neural Oscillators Modular Exoskeleton

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Intelligent Process Automation: the Future of Digital Transformation 10

Intelligent Process Automation: The Future of Digital Transf...

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

作者： Kholiya, Pankaj Singh Kapoor, Akshat Rana, Meghavi Bhushan, Megha DIT University School of Computing Dehradun India

ISBN: (纸本)9781665439701

the technological evolution in the last decades has led us to the forefront of the digitization of services at every stratum of the processes and businesses. As the technology is advancing, an era of automation is witnessed in each field. Intelligent Process Automation (IPA) is amalgamation of Robotic Process Automation (RPA) with Artificial Intelligence with a view to create end-to-end processes which can think, learn, and adapt on their own. this paper aims to present a comprehensive study of the RPA tools associated to the intelligent automation using Artificial Intelligence. It also provides a brief overview of the current development in IPA market which can contribute to the implementation of the IPA in various organizations. © 2021 IEEE.

关键词： Process control

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Using Distributed Tracing to Identify Inefficient Resources Composition in Cloud Applications 10

Using Distributed Tracing to Identify Inefficient Resources ...

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

作者： Casse, Clement Berthou, Pascal Owezarski, Philippe Josset, Sebastien Univ Toulouse LAAS CNRS CNRS Toulouse France Orange Toulouse France Univ Toulouse LAAS CNRS UPS Toulouse France

ISBN: (纸本)9781665435383

Cloud-Applications are the new industry standard way of designing Web-Applications. With Cloud computing, Applications are usually designed as microservices, and developers can take advantage of thousands of such existing microservices, involving several hundred of cross-component communications on different physical resources. Microservices orchestration (as Kubernetes) is an automatic process, which manages each component lifecycle, and notably their allocation on the different resources of the cloud infrastructure. Whereas such automatic cloud technologies ease development and deployment, they nevertheless obscure debugging and performance analysis. In order to gain insight on the composition of services, distributed tracing recently emerged as a way to get the decomposition of the activity of each component within a cloud infrastructure. this paper aims at providing methodologies and tools (leveraging state-of-the-art tracing) for getting a wider view of application behaviours, especially focusing on application performance assessment. In this paper, we focus on using distributed traces and allocation information from microservices to model their dependencies as a hierarchical property graph. By applying graph rewriting operations, we managed to project and filter communications observed between microservices at higher abstraction layers like the machine nodes, the zones or regions. Finally, in this paper we propose an implementation of the model running on a microservices shopping application deployed on a Zonal Kubernetes cluster monitored by Open Telemetry traces. We propose using the flow hierarchy metric on the graph model to pinpoint cycles that reveal inefficient resource composition inducing possible performance issues and economic waste.

关键词： Distributed Tracing Cloud computing Property Graph Graph Rewriting Hierarchical Model

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Intelligent Information Processing IX 1

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丛书名： IFIP Advances in Information and Communication Technology

1000年

作者： Zhongzhi Shi Eunika Mercier-Laurent Jiuyong Li

ISBN: (数字)9783030008284

ISBN: (纸本)9783030008277;9783030131470

this book constitutes the refereed proceedings of the 10th IFIP TC 12 international conference on Intelligent Information Processing, IIP 2018, held in Nanning, China, in October 2018.;the 37 full papers and 8 short papers presented were carefully reviewed and selected from 80 submissions. they are organized in topical sections on machine learning, deep learning, multi-agent systems, neural computing and swarm intelligence, natural language processing, recommendation systems, social computing, business intelligence and security, pattern recognition, and image understanding.

关键词： Artificial Intelligence Information Systems and Communication Service Image Processing and Computer Vision Computer Communication Networks Systems and Data Security

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Machine Learning Comparative Analysis for Plant Classification 13th

Machine Learning Comparative Analysis for Plant Classificati...

引用

13th international conference on Application of Fuzzy Systems and Soft computing (ICAFS)

作者： Imanov, Elbrus Alzouhbi, Abdallah Khaled Near East Univ Dept Comp Engn TR-10 Mersin North Cyprus Turkey Dept Water Recycling Machha 1032 Akkar Lebanon

ISBN: (纸本)9783030041649

Nowadays, digital image processing, artificial neural network and machine visualization have been pettishly progressing, and they cover a significant side of artificial cleverness and the rule among human beings and electro-mechanical devices. these technologies have been utilized in a wide range of agricultural operations, medicine and manufacturing. By this research the preparation of some functions has been conducted. In this paper we introduce the classification of maize leaves from pictures that reveal many conditions, opening among pictures, by pre-processing, taking out, plant feature recognition, matching and training, and lastly getting the outcomes executed by Matlab, neural network pattern recognition application. these given features are separated to leaf maturity and picture interpretations, rotary motions and calibration, and they are calculated to develop an approach that gives us better classification algorithm results. A plant scientist may be introduced with a plant for recognition of its classes revealed in its natural home ground, to gather an in-depth recognition.

关键词： Artificial neural network Digital image processing Machine visualization classification K-nearest neighbor Support vector machine Machine learning

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Machine Learning Approaches for Emotion recognition: A Comparative Study 12

Machine Learning Approaches for Emotion Recognition: A Compa...

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12th international conference on Current Trends in Advanced computing, ICCTAC 2024

作者： Singh, Himanshu Singh, Arushi Chauhan, Priyaj Kamboj, Deepika IT KIET Group of Institution Ghaziabad India CSIT KIET Group of Institution Ghaziabad India

ISBN: (纸本)9798350395808

A key component that has arisen in[10] human-computer interaction, artificial intelligence, and affective computing is the ability to recognize emotions. the objective of the research project is to examine a method that is integrated for the recognition of facial expressions of emotion. Humans transmit their emotions through indirect and non-verbal means most of the time. their sentiments are communicated through these methods. Providing a complete overview that includes an assessment of all the important emotion detection methods that can be found in a single region is the objective of the exposition that is now being presented. the paper represents the first attempt to offer an overview of all the emotion detection models that have been developed for the previous 10 years. the document contains an in-depth analysis of the technique as well as the datasets. For face identification, the technique makes use of the local Binary pattern Histogram (LBPH), Convolutional Neural Networks (CNN) for feature extraction, and the Deep Face model for comprehensive emotion analysis. © 2024 IEEE.

关键词： Local binary pattern

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