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检索条件"任意字段=Proceedings of the 2023 4th International Conference on Machine Learning and Computer Application"

共 4179 条记录，以下是3631-3640 订阅

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2019 4th international Seminar on computer Technology, Mechanical and Electrical Engineering, ISCME 2019 - 1. computer Network and Information Security Technology

2019 4th International Seminar on Computer Technology, Mecha...

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2019 4th international Seminar on computer Technology, Mechanical and Electrical Engineering, ISCME 2019

the proceedings contain 278 papers. the topics discussed include: deceptive jamming recognition based on wavelet entropy and RBF neural network;the communication network scheme based on EPON and industrial Ethernet technology for smart distribution network;the effect of region-based message selective delivery strategy on post-disaster emergency network;analyzing the efficiency and robustness of gossip in different propagation processes with simulations;analysis of and reflections over the development of new energy automobile and intelligent manufacturing;construction of experiential learning space model based on virtual reality technology;design and implementation of a simulation training platform for performance measurement of a radar transmitter sub-system;hybrid energy storage control method for isolated island AC micro-grid based on consistency theory;parameter matching and simulation optimization analysis of electric vehicle power system;game problem and Nash equilibrium in the electronic payment market with multi-agent participation;optimization framework and application research of automatic test system for armored vehicles;and improved SVM algorithm for upper limb rehabilitation mechanical arm study on the prediction of track tracking control.

关键词： Military vehicles

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application of deep learning and compressed sensing for reconstruction of images 1

Application of deep learning and compressed sensing for reco...

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1st international conference on Advances in Physical Sciences and Materials 2020, ICAPSM 2020

作者： Hanumanth, P. Bhavana, P. Subbarayappa, Shreyanka Department of Computer Science and Engineering M S Ramaiah University of Applied Sciences #470-P 4th Phase Peenya Industrial Area Bengaluru KA560058 India Department of Electronic and Communication Engineering M S Ramaiah University of Applied Sciences #470-P 4th Phase Peenya Industrial Area Bengaluru KA560058 India Electrical Engineering Department University of Texas at Arlington ArlingtonTX76019 United States

Compressed sensing (CS) is a technique in signal processing which reconstructs any given signal at a rate less than that of Nyquist's' rate given that the signal is sparse and incoherent in nature. the main focus of CS is to find a random matrix which reconstructs the original signal using as few samples as possible. In recent years there has been a lot of interest in using CS to reconstruct 2D images. Several machine learning and deep learning algorithms have been proposed for finding the random matrix. However, using deep learning techniques to generate the random matrix is still an emerging concept. there are several papers exploring the concepts of deep learning with compressed sensing for images and have produced promising results. the results obtained in these papers warrant a comparison to analyze their performances against more traditional methods to determine the best approach to reconstruct images. these results are also compared with the popular JPEG and JPEG2000 codecs. this paper focuses on surveying deep learning algorithms for reconstruction of images using CS. the comparison reveals that deep learning algorithms perform significantly better than traditional methods and perform well when compared to any image compression codec like JPEG. Possible methods to improve the existing algorithms have been suggested. © Published under licence by IOP Publishing Ltd.

关键词： Compressed sensing

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Convolutional Dictionary learning Using Global Matching Tracking (CDL-GMT): application to Visible-Infrared Image Fusion 4

Convolutional Dictionary Learning Using Global Matching Trac...

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4th Annual international conference on Data Science and Business Analytics, ICDSBA 2020

作者： Zhang, Chengfang Sichuan Police College Luzhou646000 China

ISBN: (纸本)9781728181646

the traditional convolutional dictionary-learning algorithm not only realizes the global sparse representation by imposing constraints on the image 0 or 1 norm, but also allows all possible movements of the local dictionary. However, selected atoms may be concentrated in certain areas of the image, while other atoms may be very sparse. therefore, when using a traditionally-learned convolution dictionary, global sparseness alone is not sufficient to represent the entire image structure, and the resulting fusion image suffers from partial detail damage. For the above-mentioned convolutional sparse coding problem, this paper presents a greedy strategy based on the constraint 1_("0,"∞) problem to obtain a convolution dictionary(CDL-GMT), and applies the learned convolutional sparse dictionary to infrared and visible-light image fusion. this method attempts to impose constraints on sparsity locally, while considering the global structure. Experimental results prove the method to be superior to others in subjective and objective evaluation. © 2020 IEEE.

关键词： Convolution

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2019 4th international Seminar on computer Technology, Mechanical and Electrical Engineering, ISCME 2019 - Preface

2019 4th International Seminar on Computer Technology, Mecha...

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2019 4th international Seminar on computer Technology, Mechanical and Electrical Engineering, ISCME 2019

关键词： Military vehicles

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2019 4th international Seminar on computer Technology, Mechanical and Electrical Engineering, ISCME 2019 - 5. Power Electronics and Smart Grid

2019 4th International Seminar on Computer Technology, Mecha...

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2019 4th international Seminar on computer Technology, Mechanical and Electrical Engineering, ISCME 2019

关键词： Military vehicles

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2019 4th international Seminar on computer Technology, Mechanical and Electrical Engineering, ISCME 2019 - 2. Advanced Algorithm and Artificial Intelligence

2019 4th International Seminar on Computer Technology, Mecha...

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2019 4th international Seminar on computer Technology, Mechanical and Electrical Engineering, ISCME 2019

关键词： Military vehicles

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2019 4th international Seminar on computer Technology, Mechanical and Electrical Engineering, ISCME 2019 - 3. Signal Processing and Pattern Recognition

2019 4th International Seminar on Computer Technology, Mecha...

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2019 4th international Seminar on computer Technology, Mechanical and Electrical Engineering, ISCME 2019

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application of Blockchain Technology in Credit Management for Credit Bank System 20

Application of Blockchain Technology in Credit Management fo...

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proceedings of the 2020 4th international conference on Electronic Information Technology and computer Engineering

作者： Guoxia Zou Yunlan Xue School of Artificial Intelligence The Open University of Guangdong (Guangdong Polytechnic Institute) Guangzhou China

ISBN: (纸本)9781450387811

Credit bank provides learning channels and direction for growing talents, but the current centralized management form of credit bank is not conducive to the management of learning results. the blockchain technology can solve the problem of credit management in credit bank system. the course, students and the results of their learning are linked to the block by the blockchain technology. It can realize the decentralization of management, the automation of transfer about learning credit and education, results are traceable and it cannot be tampered with, so blockchain technology can save management resources of credit bank and improve trust. It is feasible that using hyperledger fabric technology to realize the credit management of credit bank system by system design and experiment.

关键词： Blockchain Hyperledger Fabric Credit Bank

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Video Smoke Detection for Surveillance Cameras Based on Deep learning in Indoor Environment 4

Video Smoke Detection for Surveillance Cameras Based on Deep...

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4th international conference on Recent Advances in Signal Processing, Telecommunications and Computing, SigTelCom 2020

作者： Nguyen, Viet thang Quach, Cong Hoang Pham, Minh Trien Vnu University of Engineering and Technology Ha Noi Viet Nam

ISBN: (纸本)9781728168661

An early fire detection in indoor environment is essential for people's safety. During the past few years, many approaches using image processing and computer vision techniques were proposed. However, it is still a challenging task for application of video smoke detection in indoor environment, because the limitations of data for training and lack of efficient algorithms. the purpose of this paper is to present a new smoke detection method by using surveillance cameras. the proposed method is composed of two stages. In the first stage, motion regions between consecutive frames are located by using optical flow. In the second stage, a deep convolutional neural network is used to detect smoke in motion regions. Besides, to overcome the problem of lacking data, simulated smoke images are used to enrich the dataset. the proposed method is tested on our data set and real video sequences. Experiments show that the new method is successfully applied to various indoor smoke videos and significant for improving the accuracy of fire smoke detection. Source code and the dataset have been made available online. © 2020 IEEE.

关键词： Smoke

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Visual Social Distance Alert System Using computer Vision Deep learning 4

Visual Social Distance Alert System Using Computer Vision De...

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4th international conference on Electronics, Communication and Aerospace Technology, ICECA 2020

作者： Degadwala, Sheshang Vyas, Dhairya Dave, Harsh Mahajan, Arpana Sigma Institute of Engineering Department of Computer Engineering Vadodara India Shree Drashti Infotech Llp Vadodara India Smt. B.K. Shah Medical Institute Research Center Vadodara India Madhav University Rajasthan India

ISBN: (纸本)9781728163871

One of the principles and best measures to contain the ongoing viral episode is the support of the alleged social distancing (SD). To agree to this limitation, governments are receiving limitations over the base between close to home separation between individuals. Given this real situation, it is critical to enormously gauge the consistence to such physical requirement in our life, so as to make sense of the purposes behind the potential breaks of such separation impediments and comprehend if this suggests a likely danger. To this end, the proposed research work presents the Video Social Distancing issue, characterized as the programmed assessment of the between close to home good ways from a picture, and the portrayal of related individuals' conglomerations. Video Social Distancing is significant for a non-obtrusive investigation of whether individuals follow the Social Distancing limitation, and to give insights about the degree of security of explicit territories at whatever point this imperative is abused. It has been first viewed that, estimating Video Social Distancing isn't just a mathematical issue, however it additionally infers a more profound comprehension of the social conduct in the scene. the point is to genuinely identify possibly risky circumstances while keeping away from bogus alerts (e.g., a family with youngsters or family members, a senior with their guardians), the entirety of this by following current security strategies. At that point, the proposed research work will discuss about how video social distancing is related with past writing in social signal processing and show a way to investigate new computer vision techniques that can give an answer for such issue. this paper is concluded with future moves that are identified with the viability of video social distancing frameworks, moral ramifications and future application situations. © 2020 IEEE.

关键词： computer vision

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