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检索条件"任意字段=International Conference on Signal Image Technology and Internet Based Systems"

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A Hybrid image Edge Detection Approach for the images of Tocklai Vegetative Tea Clone Series TV1, TV9, TV10 of Assam 7th

A Hybrid Image Edge Detection Approach for the Images of Toc...

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7th international conference on Information and Communication technology for Intelligent systems, ICTIS 2023

作者： Begum, Jasmine Ara Sarmah, Ranjan Assam Rajiv Gandhi University of Cooperative Management Sivasagar India

ISBN: (纸本)9789819937578

Edge Detection technique within image segmentation process serves as the significant step for identification of the edges of various images of Tocklai Vegetative Tea Clone Series TV1, TV9 and TV10 of Assam. Such technique is basically used to identify the discontinuities in image. There are several edge detection technique used in image Processing and identifying the suitable edge detection technique for the identification process is a major concern. The present work thus focuses on a hybrid edge detection approach which combines Canny and Sobel edge Detection Technique. The hybrid approach in order to eradicate flaws in the segmented image and to get better information on the boundaries of the images of TV1, TV9 and TV10 uses Dilation Morphological operation. A comparison is finally made with the most popular edge detection techniques like Sobel, Prewitt, Robert, Canny, Laplacian of Gaussian based upon noise level parameters such as Mean Square Error (MSE), Peak signal noise Ratio (PSNR) and SNR (signal Noise Ratio). The analysis output obtained through comparison draws a conclusion that hybrid edge detection approach when combined with dilation of the morphological operation shows efficient outcome and can be extensively used for detecting the edge of Tocklai Vegetative Tea clone series of Assam. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Edge detection

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Proposed HCDNA for Enhancing the Security of Marine Environment IoT systems 10

Proposed HCDNA for Enhancing the Security of Marine Environm...

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10th international Japan-Africa conference on Electronics, Communications, and Computations, JAC-ECC 2022

作者： Ahmed, Tokka Elsayed Raslan, Walid A. Ghouniem, Atif Abdel-Atty, Heba M. Suez Canal University Faculty of Engineering Communication Engineering Department Ismailia Egypt Delta University for Science and Technology Faculty of Engineering Electronics and Communications Department Gamsaa Egypt Port Said University Faculty of Engineering Electrical Engineering Department Port Said42524 Egypt

ISBN: (纸本)9781665464635

Recently, the shipping industry and marine operations have been intensively reliable on the internet of things (IoT).IoT devices are used for the automation of shipping operations cargo tracking and security monitoring of the ships. In this paper, we focus on maintaining efficient security levels for marine communications. We propose new cryptographic methods based on the hyperchaotic sequence and the DNA sequence for image encryption. The proposed algorithm is applied to a smart buoy to enhance the security of the transmitted image through IoT systems in shipping industry monitoring. In addition, we evaluate and analyze the performance of three existing encryption algorithms for IoT (Blowfish, Advanced Encryption Standard (AES), and international Data Encryption Algorithm (IDEA)). Furthermore, a comparison was conducted between the three existing algorithms and the proposed one in terms of encryption time, correlation coefficient, and entropy before and after encryption. The simulation experiments show that the proposed cryptographic method outperforms the three existing algorithms in terms of quality, security, and robustness against noise as well as overall performance. © 2022 IEEE.

关键词： internet of things

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Impact of training data on LMMSE demosaicing for Colour-Polarization Filter Array

Impact of training data on LMMSE demosaicing for Colour-Pola...

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international IEEE conference on signal-image Technologies and internet-based System

作者： Ronan Dumoulin Pierre-Jean Lapray Jean-Baptiste Thomas Ivar Farup IRIMAS UR 7499 Université de Haute-Alsace Mulhouse France dpt IEM IMVIA EA 7535 Université de Bourgogne Dijon France Department of Computer Science Norwegian University of Science and Technology (NTNU) Gjøvik Norway

Linear minimum mean square error can be used to demosaic images from a colour-polarization filter array sensor. However, the role of training data on its performance is yet an open question. We study the model selection using crossvalidation techniques. The results show that the training model converges quickly, and that there is no significant difference in training the model with more than 12 images of approximately 1.5 megapixels. We also found that the selected trained model performs better compared to a dedicated Colour-Polarization Filter Array demosaicing algorithm in terms of Peak signal-to-Noise Ratio.

关键词： Training Maximum likelihood detection PSNR Databases Array signal processing Training data Nonlinear filters

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Abnormal Behavior Detection in Electronic-Exam Videos Using BeatGAN 8

Abnormal Behavior Detection in Electronic-Exam Videos Using ...

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8th international Iranian conference on signal Processing and Intelligent systems, ICSPIS 2022

作者： Atabay, Habibollah Agh Hassanpour, Hamid Shahrood University of Technology Image Processing & Data Mining Lab Shahrood Iran

ISBN: (纸本)9781665476232

Abnormal Behavior Detection is a core ability to recognize cheating in electronic exams (e-exams), especially in the scenes where a fraudulent candidate hides unauthorized resources from the view of the proctor. This work utilizes the BeatGAN algorithm to detect behavioral abnormalities in the skeleton-based motion information of candidates during remote e-exams. We examine the algorithm on the previously published dataset of skeleton features extracted from e-exam videos. The results show that BeatGAN outperforms previously investigated algorithms in sequence anomaly detection using the raw joint-coordinate, implicit bone-length-and-angle and explicit bone-length feature types. But, in event anomaly detection, BeatGAN does not improve the state-of-the-art results on the dataset. © 2022 IEEE.

关键词： Anomaly detection

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Proceedings - 2022 IEEE international conference on Energy internet, ICEI 2022

Proceedings - 2022 IEEE International Conference on Energy I...

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6th IEEE international conference on Energy internet, ICEI 2022

ISBN: (纸本)9781665493277

The proceedings contain 31 papers. The topics discussed include: large-signal modeling for full-bridge LLC resonant converter using extended hyperbolic tangent function;portfolio strategy of power producer considering energy storage in spot market, ancillary market and option market;multi-period two-stage stochastic der aggregation for power flexibility reserve;distributed photovoltaic-storage system optimization planning considering flexible resources in smart distribution network;echo state network based noise detection in energy internet orienting justice blockchain data;joint bidding strategy of onsite energy storage subject in multi-market collaborated with wind power plants;intelligent control technology of air source heat pump for mango drying;a bidirectional converter stabilization control strategy for novel power systems;and analysis of carbon emission reduction potential of regional multi-energy system considering the influencing factors of carbon emissions.

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12th international conference on Broadband Communications, Networks, and systems, BROADNETS 2021

12th International Conference on Broadband Communications, N...

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12th international conference on Broadband Communications, Networks, and systems, BROADNETS 2021

ISBN: (纸本)9783030934781

The proceedings contain 24 papers. The special focus in this conference is on Broadband Communications, Networks, and systems. The topics include: Road Rage Recognition System based on Face Detection Emotion;a Drip Irrigation Remote Control System Using 5G-IoT technology;Multipath QUIC – Directions of the Improvements;ARTI: One New Adaptive Elliptical Weighting Model Combining with the Tikhonov-p-norm for image Reconstruction;Calculation and Numerical Simulation of Building Integrated Photovoltaic System based on BIM technology;connected Autonomous Vehicle Platoon Control Through Multi-agent Deep Reinforcement Learning;accurate Estimation on the State-of-Charge of Lithium-Ion Battery Packs;Fire Simulation and Optimal Evacuation based on BIM technology;Discrete Sliding Mode Control of PMSM with Network Transmission;end-to-End Dynamic Pipelining Tuning Strategy for Small Files Transfer;smart Medical and Nursing Platform based on 5G technology;time-Domain Predictable Trajectory Planning for Autonomous Driving based on internet of Vehicles;Rate-Compatible Shortened Polar Codes based on RM Code-Aided;research on Wheat Impurity image Recognition based on Convolutional Neural Network;based on Energy Router Energy Management Control Strategy in Micro-grid;containers’ Privacy and Data Protection via Runtime Scanning Methods;digital Twin for Cybersecurity: Towards Enhancing Cyber Resilience;differential Privacy-based Permissioned Blockchain for Private Data Sharing in Industrial IoT;Efficient Privacy-Preserving User Matching with Intel SGX;developing an Online Examination Timetabling System Using Artificial Bee Colony Algorithm in Higher Education;a Topology-Aware Scheduling Strategy for Distributed Stream Computing System;a Data Stream Prediction Strategy for Elastic Stream Computing systems.

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Electromagnetic signal Augmentation of Pantograph Arcs Using an Improved DCGAN

Electromagnetic Signal Augmentation of Pantograph Arcs Using...

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Information systems and Computing technology (ISCTech), international conference on

作者： Chunhui Zhang Yanyue Liang Zhiwei Gao Li Zhao School of Artificial Intelligence Shijiazhuang Institute Of Technology Shijiazhuang China School of Internet Application Technology Shijiazhuang Institute Of Technology Shijiazhuang China Hebei Province Key Laboratory of Electromagnetic Environment Effecs and Information Processing Shijiazhuang Tiedao University Shijiazhuang China Shijiazhuang Institute Of Technology Shijiazhuang China School of Traffic and Transportation Shijiazhuang Tiedao University Shijiazhuang China

ISBN: (数字)9798350379860

ISBN: (纸本)9798350379877

In response to the insufficient sample issue in the electromagnetic signal data of high-speed railway pantograph arcs, this study proposes an improved Deep Convolutional Generative Adversarial Network (DCGAN) to augment image datasets. By optimizing the network structure, the proposed method significantly improves the quality of generated images and introduces a lightweight design that reduces the computational demands of the model, making it more suitable for resource-constrained environments. After 5,000 iterations, the proposed method achieves a Fréchet Inception Distance (FID) score of 36.33, compared to 45.54 for the original DCGAN and 50.21 for the WGAN. Moreover, the Inception Score (IS) of the proposed method is 1.91 ± 0.11, outperforming the original DCGAN (1.81 ± 0.23) and WGAN (1.77 ± 0.04), further demonstrating its effectiveness. This method provides a new technical reference for research on electromagnetic signals in high-speed railways.

关键词： Convolution Computational modeling Noise Generative adversarial networks Rail transportation Robustness Real-time systems Electromagnetics signal analysis Optimization

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Contrast Enhancement and ROI detection in satellite images Application to the environment and sustainable development

Contrast Enhancement and ROI detection in satellite images A...

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international conference on image and signal Processing and their Applications (ISPA)

作者： Aicha Mehidi Malika Mimi Abdallah Mehidi Soraya Zehani Electrical Engineering Department Laboratory of Signals and Systems Faculty of Sciences and Technology University of Abdelhamid Ibn Badis Mostaganem Algeria Laboratory of Signals and Systems Faculty of Sciences and Technology University of Abdelhamid Ibn Badis Mostaganem Algeria Electrical Engineering Department Laboratory of Vision and Communication Systems Faculty of Sciences and Technology University of Biskra

ISBN: (数字)9798350309249

ISBN: (纸本)9798350309256

During the last few years, remote sensing is considerably used for Earth observation for the environment and sustainable development. The temporal classes of satellite images provide better information for monitoring the earth's surface at different scales; therefore these images are becoming a very relevant opportunity of investigating. The numerical analyses of image processing are based on the artificial intelligence (AI) tool rather than the traditional methods. The environmental indicators from these images offer very important statistics, the carried out work of dynamic phenomena, the observation event and interpretation of evolving circumstances like: atmospheric conditions, crises and natural disasters taking the opportunity to be studied, several problems come out of deforestation and monitoring of water resources (water bodies). The purpose of this study is focused on drawing out details from the database used and then to give an offer for a texture analysis strategy. Firstly, using specific development and then developing the existing software in the second hand. This work is to establish an algorithm for the detection of region of interest (water body) which is based on the theory of fuzzy logic and the hypothesis of Fuzzy C-Means.

关键词： Earth image segmentation Software algorithms signal processing algorithms Satellite images Sustainable development Artificial intelligence

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Proceedings - 2022 international conference on Information Processing and Network Provisioning, ICIPNP 2022

Proceedings - 2022 International Conference on Information P...

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2022 international conference on Information Processing and Network Provisioning, ICIPNP 2022

ISBN: (纸本)9781665464055

The proceedings contain 35 papers. The topics discussed include: research on preventive maintenance of industrial internet based on reinforcement learning;micro-doppler effect of ship based on pendulum oscillation model;leveraging graph attention network for SDN routing performance prediction;discussion on 6G network architecture based on evolution;airship-launched multi-channel receiver design based on lora technology for typhoon information;intelligent deployment of multi-air base stations for capacity enhancement of emergency communications;DFCNI: researching on data-centric framework of cloud network integration for telecom operators;analysis of spectrum refarming methods for 5G network deployment;research on microwave imaging of airborne antenna;research on interconnection architecture for 5G inter-networks roaming;a study of remote sensing image ground segmentation on deep learning;and range imaging of integrated radar communication signal based on OFDM.

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A Secret image Sharing Method based on Shared Matrix and Variational Hyperprior Network 2

A Secret Image Sharing Method Based on Shared Matrix and Var...

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2nd international conference on Networking systems of AI, INSAI 2022

作者： Ding, Yuxin Shao, Miaomiao Nie, Cai Computer Science and Technology Shenzhen China

ISBN: (纸本)9781665491785

At present people can easily share multimedia information on internet, which leads to serious data security issues. Especially in medical, military and financial fields, images always contain a lot of sensitive information. To safely transmit images among people, many secret image sharing methods are proposed. However, the existing methods can not solve the problems of pixel expansion and high computational complexity of shadow images at the same time. In this paper, we propose an image sharing method by combining sharing matrix and variational hyperprior network, to reduce the pixel expansion and computational complexity of secret image sharing methods. The method uses the variational hyperprior network to encode images. It introduces the hyperprior to effectively catch spatial dependencies in the latent representation, which can compress image with high efficiency. The experimental results show that our method has low computational complexity and high security performance compared with the state-of-the-art approaches. In addition, the proposed method can effectively reduce the pixel expansion when using the sharing matrix to generate shadow images. © 2022 IEEE.

关键词： Computational complexity

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