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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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An attempt at the possibility of using multi-output paraunitary filters for image processing for astrophotography trackers 27

An attempt at the possibility of using multi-output paraunit...

引用

27th international conference on Knowledge based and Intelligent Information and Engineering Sytems, KES 2023

作者： Poczekajlo, Pawel Suszynski, Robert Koszalin University of Technology ul Sniadeckich 2 Koszalin75-453 Poland

The article deals with the issue of stabilizing the frame position of the shot in long time astrophotography. The authors described this issue from the point of view of guiding a telescope following of the sky, and also in terms of the possibility of supporting this process with digital signal processing using paraunitary filters. The procedure for obtaining a 2D paraunitary system from an initial (preset) filter is presented. An attempt is made to verify the data that can be obtained from individual outputs of paraunitary systems. Several example filters were shown and their operation was tested on a selected image of a real astronomical object from the telescope's guide camera. based on the output images obtained (from three paraunit systems), the possibility of their further use in practice was evaluated. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： astrophotography filters 2D images processing multioutput filters orthogonal filters paraunitary filters trackers

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DopeNet: Range-Doppler Radar-based UAV Detection Using Convolutional Neural Network 14

DopeNet: Range-Doppler Radar-based UAV Detection Using Convo...

引用

14th international conference on Ubiquitous and Future Networks, ICUFN 2023

作者： Aouto, Ali Jun, Taesoo Lee, Jae-Min Kim, Dong-Seong Kumoh National Institute of Technology Networked Systems Lab. Dept. of It Convergence Engineering Gumi Korea Republic of

ISBN: (纸本)9798350335385

The proliferation of commercial unmanned aerial vehicles (UAVs) of various sizes and shapes, equipped with cameras and even signal sabotage devices, has raised concerns regarding privacy and safety. Some websites even offer weapons that can be attached to drones, adding to the security threats. As a result, researchers have been motivated to develop an intelligent system that can be integrated into surveillance systems to classify unauthorized UAVs that are flying in restricted areas. In this paper, we propose a convolutional neural network (CNN) for UAV detection based on Radar image data. The Radar system, called Real Doppler RAD-DAR (Radar with Digital Array Receiver), is a range-doppler system developed by the Microwave and Radar Group. We construct and analyze the CNN by adjusting its hyper-parameters using the RAD-DAR dataset. Our simulation results show that setting the number of filters to 32 results in the best time-wise accuracy. The network achieved an accuracy of 97.63%, which is higher than other benchmark image classifiers. Additionally, we conducted an ablation study to investigate and validate the contribution of each part of the neural network. © 2023 IEEE.

关键词： image classification

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Design and Implementation of image Copyright Protection System based on Chinese Cryptographic Algorithms 7

Design and Implementation of Image Copyright Protection Syst...

引用

7th international conference on signal and image Processing, ICSIP 2022

作者： Cai, Zengyu Si, Yajie Zhang, Jianwei Wang, Jingchao Zhengzhou University of Light Industry School of Computer and Communication Engineering Zhengzhou China Zhengzhou University of Light Industry School of Software Engineering Zhengzhou China

ISBN: (数字)9781665495639

ISBN: (纸本)9781665495639

With the sharp increase in the number of netizens, people's online life is becoming richer and richer, the behavior of stealing pictures on the internet is more rampant, and online image infringements continue to occur, so the protection of image copyright is particularly important. This paper first introduces the relevant background knowledge of Chinese cryptographic algorithms, image copyright protection and image steganography technology;secondly, the overall design scheme of the system is proposed, including functional design, hierarchical pattern design and system flow design;then, the key technologies of the system implementation are introduced;finally, test and analyze the system. The test results show that the system can secretly write the image copyright information encrypted by the SM2 algorithm into the image through the LSB algorithm, so as to achieve the purpose of image copyright protection without affecting the beauty of the image. © 2022 IEEE.

关键词： Copyrights

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image Filtration using Graph-based Low Pass Filter 1

Image Filtration using Graph-based Low Pass Filter

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1st international conference on Recent Trends in Microelectronics, Automation, Computing and Communications systems, ICMACC 2022

作者： Sonti, Nagaraju Rukmini, M.S.S. Pamulapati, Venkatappa Reddy Vignan's Foundation for Science Technology & Research Department of Ece Andhra Pradesh Vadlamudi India

ISBN: (纸本)9781665496049

This paper is based on filtering various noises from the image data through the graph-based low pass filter. The linear noise (salt & pepper noise) and nonlinear noise (Gaussian noise) are taken for the research purpose, those noises are randomly added to the image data. In this paper, the graph filter is proposed to remove the linear as well as non-linear noise. This graph-based low pass filter also allows the noise from the bulk image dataset. In the graph-based low pass filter, the image dataset is converted into a structure like a graph and then the image is considered as matrix data. The pixels in the data connected with neighboring pixels that demonstrate the direction and position of the pixel with a connection of neighboring pixels results in angle. These two properties made Graph signal Processing more adaptable for image data. In the simulation, the performance of proposed model is compared with the three conventional filters (Volterra filter, median filter, and stack filters). The performance measurements of the models are based on the Peak signal to Noise Ratio, Mean Square Error, Root means square error, and Structural similarity index. © 2022 IEEE.

关键词： Median filters

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Wi-Fi Received signal Strength-based Indoor Localization System Using K-Nearest Neighbors fingerprint integrated D*algorithm 24

Wi-Fi Received Signal Strength-based Indoor Localization Sys...

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24th international conference on Advanced Communication technology (ICACT) - Artificial Intelligence Technologies toward Cybersecurity

作者： Jarawant, Tanatthep Kamsingt, Patcharin Torteekat, Peerapong Manuthasnat, Shariff Hematulint, Warunyu Choorakst, Tachodom Phisannupawongt, Thaweerath Sangkarakt, Sitthirak Mungkhudt, Sookaseam Somjitt, Thanaporn King Mongkuts Inst Technol Ladkrabang Int Acad Aviat Ind Dept Aeronaut Engn Air Space Control Optimizat & Management Lab Bangkok 10520 Thailand Natl Astron Res Inst Thailand Chiang Mai 50180 Thailand

ISBN: (纸本)9791188428090

The indoor localization system is essential since the Global Positioning System cannot give an accurate position indoors, especially when several floor plans are considered. Wi-Fi received signal strength becomes an alternative indicator for indoor localization systems. The experiment proposed a localization system created by integrating and working between the K-Nearest Neighbors algorithm and the D*algorithm. The result illustrates the optimal path from the start point to the target point by avoiding the obstacle performing exceptionally well. The K-Nearest Neighbors algorithm provide the result for localization with Root Mean Square Errors of displacement at 1.190 meters, 2.491 meters, and 1.363 meters of X-Axis Y-Axis, respectively. The proposed indoor localization system can have various applications considering different environmental factors in different applications, such as the size of unmanned aerial vehicles when applying indoor unmanned aerial vehicles.

关键词： Indoor localization Wi-Fi Received signal Strength Indicator K-Nearest Neighbor D*Algorithm Indoor positioning

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The Analysis of Network Course in Intelligent image Acquisition Education System based on Deep Learning

The Analysis of Network Course in Intelligent Image Acquisit...

引用

signal Processing, Communications and Engineering Management conference (ISPCEM), international

作者： Qianqian Ge Cuncun Wei Dongyan Wu Zhejiang Business Technology Institute Ningbo China

ISBN: (数字)9798331528676

ISBN: (纸本)9798331528683

The internet, big data, and intelligent robots have transformed online education. This study introduces an Enhanced Convolutional Neural Network (CNN+) model optimized with refined weight initialization and strategic activation functions for image recognition. The CNN+ model achieves 99.5% accuracy on MNIST and 75.2% on CIFAR-10, with the Sigmoid-ReLU hybrid boosting performance to 99.2% and 72.3% respectively. These optimizations underscore the importance of strategic CNN architecture choices in enhancing performance, supporting advancements in online education platforms. The CNN+ model represents a significant breakthrough in image recognition for online education.

关键词： image recognition Accuracy Education Neural networks Optimization methods signal processing Stability analysis internet Convolutional neural networks Intelligent robots

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A Special-Purpose Video Streaming Codec for internet-based Remote Driving

A Special-Purpose Video Streaming Codec for Internet-based R...

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IEEE/ASME (AIM) international conference on Advanced Intelligent Mechatronics

作者： Neel Adwani Kevin Silvestrini-Cordero Roberto Rojas-Cessa Tao Han Cong Wang Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

ISBN: (数字)9798350355369

ISBN: (纸本)9798350355376

Real-time teleoperation of robotic systems over the internet is a desirable technology in many ways. Latency of the video feedback has been hampering its development. This paper takes the application of remote driving to introduce an unconventional codec that provides a very low latency for internet-based video streaming. The proposed method preserves just enough information in the video for essential perception and decision making of a remote driver. Thanks to a unique integration of several image processing and data streaming techniques, the proposed codec can realize a glass-to-glass latency of around 90 ms. A series of tests are conducted over the real consumer internet to analyze the latency and verify the effectiveness of remote driving with the proposed codec.

关键词： Codecs Mechatronics image processing Decision making Streaming media Real-time systems internet

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2023 7th international conference on Communication and Information systems An Improved IOTA Protocol based on Optimal Midway Walk 7

2023 7th International Conference on Communication and Infor...

引用

7th international conference on Communication and Information systems, ICCIS 2023

作者： Wu, Hongcheng Zhi, Hui Liu, Yangyang Anhui University School of Electronic and Information Engineering Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Hefei230601 China Hefei Zhilian Technology Industry Investment Co. Ltd Hefei230601 China

ISBN: (纸本)9798350330540

IOTA (internet of Things Applications) protocol aims to provide a secure and trustworthy protocol for realizing data-value interactions between IoT devices, and it has become the next possible direction for the development of Blockchain applications. IOTA protocol has the problem that the time-consuming cumulative weight update grows too fast with the increase of the number of transactions, this paper proposed an improved IOTA protocol based on optimal midway walk, the improved protocol uses cutting-edge transaction selection algorithm of weighted Monte Carlo Markov random walk to reduce cumulative weight update delay. Firstly, this improved IOTA protocol mainly ensures the efficiency of transaction confirmation without losing the security of consensus by introducing the optimal midway walk method, i.e., the starting point of each walk is chosen to depart at an optimal location. Secondly, this paper designs the indirect verification identity record algorithm and the layer degree of confirmation principle are designed to realize the improved IOTA protocol's resilience and resistance to Parasite chain attack. The experimental results show that the improved IOTA using random function to select the midway walk starting point from i-50λ, to i-75λsubstantially solves the system computational burden problem and greatly reduces the cumulative weight update delay. © 2023 IEEE.

关键词： cumulative weight IOTA midway walk Parasite chain attack

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24th international conference on Control systems and Computer Science, CSCS 2023

作者： Brehar, Raluca Groza, Adrian Damian, Ioana Muntean, George Nicoara, Simona Delia Technical University of Cluj-Napoca Department of Computer Science Cluj-Napoca Romania 'Iuliu Hatieganu' University of Medicine and Pharmacy Emergency County Hospital Department of Ophthalmology Cluj-Napoca Romania

ISBN: (纸本)9798350313390

The image classification task is considered solved from the technical perspective: given enough data - in terms of quantity, quality and distribution - machine learning technology is able to classify various medical conditions with high performance metrics. Yet, one disadvantage is that the large majority of approaches directly target to signal the disease without considering at all the running protocols or medical guidelines used by clinicians. We address here the gap between running clinical protocols and solutions provided by computer scientists. Instead of directly target the disease, we aim the identify only the biomarkers that the physicians are looking for. We apply this approach to the age-related macular degeneration (AMD). The task is to identify biomarkers for the AMD condition by segmenting retinal optical coherence tomography (OCT) images. One relevant question regards the choice between feature based techniques versus deep learning methods. We address this question by providing a hybrid original solution that combines deep learning based retinal layer segmentation with feature based image classification used to distinguish between a particular fluid area and its neighbouring retinal areas. In this context we perform a comparative analysis of various semantic segmentation techniques which provide noticeable results for retinal layer segmentation. On the other hand, due to the low representation of some fluids in the considered benchmark dataset, we address and enhance their recognition by texture based region of interest classification. The proposed approach is a step towards developing AI systems in line with running medical protocols. © 2023 IEEE.

关键词： image classification

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DEEP image FUSION ACCOUNTING FOR INTER-image VARIABILITY 56

DEEP IMAGE FUSION ACCOUNTING FOR INTER-IMAGE VARIABILITY

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56th Asilomar conference on signals, systems, and Computers

作者： Wang, Xiuheng Borsoi, Ricardo Augusto Richard, Cedric Chen, Jie Univ Cote Azur CNRS OCA Nice France Univ Lorraine CNRS CRAN Nancy France Northwestern Polytech Univ Inst Res & Dev Shenzhen Peoples R China

ISBN: (纸本)9781665459068

Hyperspectral and multispectral image fusion (HMIF) allows us to overcome inherent hardware limitations of hyperspectral imaging systems with respect to their lower spatial resolution. However, existing algorithms fail to consider realistic image acquisition conditions, or to leverage the powerful representation capacity of deep neural networks. This paper introduces a general imaging model which considers inter-image variability of data from heterogeneous sources, and formulates the optimization problem. Then it presents a new image fusion method that, on the one hand, solves the optimization problem accounting for inter-image variability with an iteratively reweighted scheme and, on the other hand, leverages unsupervised light-weight CNN-based denoisers to learn realistic image priors from data. Its performance is illustrated with real data that suffer from inter-image variability.

关键词： Hyperspectral data multispectral data inter-image variability image fusion deep learning

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