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

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Detection of Islanding in AC Microgrid Using Random Forest And Scalogram image based Local Binary Pattern 4

Detection of Islanding in AC Microgrid Using Random Forest A...

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4th international conference on Power, Control and Computing Technologies, ICPC2T 2025

作者： Pal, Kumaresh Namrata, Kumari Akella, Ashok Kumar Meena, Veerpratap Padmanaban, Sanjeevikumar Department of Electrical Engineering National Institute of Technology Jamshedpur India Department of Electrical Engineering IT and Cybernetics University of South-Eastern Norway Porsgrunn Norway

ISBN: (纸本)9798331530402

Islanding is a significant obstacle along with excessive penetration of DG sources. The islanding could cause harm to the customers and their equipment. The ieee 1547 DG interconnection regulations stipulate that the DG must be disconnected, and the islanding must be observed within two seconds. Basically, this paper presents a novel method for detecting islanding based upon image pattern recognition using random forest (RF) classification technique is proposed. images are utilized to derive the local binary pattern (LBP) characteristics to identify non-islanding as well as islanding events. Hence, the time series signal is obtained and transformed into scalogram images at the point of common connection. These images are utilized to extract the features using LBP, which is then utilized as a feature vector input for the RF classifier for training as well as testing. It uses the total harmonics distortion (THD) characteristic of the voltage to derive scalogram image. The RF classifier's effectiveness is assessed with 5-fold cross-validations. The result from classification demonstrates that detection of islanding using RF classifier and LBP feature being used for image pattern recognition achieved excellent results with 98.89% accuracy and detection time of 158 milliseconds. © 2025 ieee.

关键词： Local binary pattern

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5th international Symposium on signal and image Processing, ISSIP 2024

5th International Symposium on Signal and Image Processing, ...

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5th international Symposium on signal and image Processing, ISSIP 2024

ISBN: (纸本)9789819795147

The proceedings contain 31 papers. The special focus in this conference is on signal and image Processing. The topics include: A Blockchain-based Secure Framework for Storage and Access of Surveillance Video Data;encountering the Challenges and Awareness of internet Security;Data-Driven Strategies for Twitter Engagement: Hashtag Recommendations and API Insights;Analyzing and Visualizing AI Decision-Making for Human-Centered Interaction and Trust;AI-ML-based Handover Techniques in Next-Generation Wireless Networks;castle Defender: Design and Implementation of Game based on Pygame;optimizing Healthcare: Enhancing Disease Management with Recommendation systems;optimizing Diabetes Prediction Models for Enhanced Health Data Processing;comparative Analysis of Classification Models Using Various Feature Sets;An Early Detection of Tomato Plant Disease with Deep Reinforcement Learning and CNN;ioT-Powered Health Monitoring System for Protecting Vital Organs Through Cloud-based Diagnosis;LASKV: Lightweight Authenticated Session Key Agreement for Video Surveillance System;Data Analyses of Factors Influencing Sustainable Adoption of Online Public Services: An Extended UTAUT Analysis in North Macedonia;a Comprehensive Review on Real-Time Campus Compass;deep Learning Approaches for Early Detection of Bovine Respiratory Diseases in Cattle;identifying Suitable Cloud Storage Services from Cross Cloud Platforms based on the Requirements;storage-Savvy Frame Recorder: Enhancing Storage Efficiency and Inspection Speed*;lossless Medical image Compression Using Block-Wise Burrows–Wheeler Transform and Modified Run Length Encoding;advancing Software Defect Detection and Prevention: Bridging Gaps in Early-Stage and Evolving Software systems;a New Way to Communicate: Deep Learning for Deaf and Dumb People;dependent Binomial: A Family of Distributions Derivable by Modifying a Base.

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A Novel Vision Transformer Approach for Driver Fatigue Detection from EEG signal with Correlation-based Channel Selection

A Novel Vision Transformer Approach for Driver Fatigue Detec...

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2024 ieee international conference on Computing, Applications and systems, COMPAS 2024

作者： Khan, Robiul Roy, Dipon Ali, Md. Wajed Refat, Kawsar Ahmed Naziullah, Shekh Pabna University of Science and Technology Department of Electrical and Electronic Engineering Pabna Bangladesh Daffodil International University Department of Computer Science Engineering Dhaka Bangladesh

ISBN: (纸本)9798331529765

Driver fatigue poses a critical threat to road safety, necessitating the development of robust detection methods to minimize traffic accidents and societal burdens. Deep neural networks have recently been effectively applied to Electroencephalography (EEG)-based driving fatigue detection. Nevertheless, most of the existing models, particularly those relying on extensive pooling, often struggle to capture long-range dependencies within images. To address this issue, we propose a Correlation-based Channel Selection (CCS) with a Vision Transformer (ViT) approach for driver fatigue detection using an EEG. Our methodology integrates a pioneering Channel Selection (CS) block to extract discriminative channels via CCS. This mechanism systematically identifies the most informative EEG channels crucial for fatigue detection. Subsequently, we leverage Continuous Wavelet Transform (CWT) to convert the selected EEG channels into a time-frequency spectral image. Finally, the resulting time-frequency spectral images, encompassing both temporal and spectral information, are concatenated and fed into the Vision Transformer (ViT) model to classify them as either normal or fatigued. The proposed model is evaluated on a publicly available EEG dataset containing recordings from twelve subjects. The model achieved superior accuracy: 95.83% for the effective selected combined subject and 99.925% for the average accuracy of each subject, demonstrating its potential for robust driver fatigue detection. © 2024 ieee.

关键词： Deep neural networks

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Semantic-Preserving Augmentation for Robust image-Text Retrieval 48

Semantic-Preserving Augmentation for Robust Image-Text Retri...

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48th ieee international conference on Acoustics, Speech and signal Processing, ICASSP 2023

作者： Kim, Sunwoo Shim, Kyuhong Nguyen, Luong Trung Shim, Byonghyo Seoul National University Department of Electrical and Computer Engineering Seoul Korea Republic of

ISBN: (纸本)9781728163277

image-text retrieval is a task to search for the proper textual descriptions of the visual world and vice versa. One challenge of this task is the vulnerability to input image/text corruptions. Such corruptions are often unobserved during the training, and degrade the retrieval model's decision quality substantially. In this paper, we propose a novel image-text retrieval technique, referred to as robust visual semantic embedding (RVSE), which consists of novel image-based and text-based augmentation techniques called semantic-preserving augmentation for image (SPAug-I) and text (SPAug-T). Since SPAug-I and SPAug-T change the original data in a way that its semantic information is preserved, we enforce the feature extractors to generate semantic-aware embedding vectors regardless of the corruption, improving the model's robustness significantly. From extensive experiments using benchmark datasets, we show that RVSE outperforms conventional retrieval schemes in terms of image-text retrieval performance. © 2023 ieee.

关键词： Semantics

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MetaLeak: Assessing image Metadata Leakage in Android Apps 21

MetaLeak: Assessing Image Metadata Leakage in Android Apps

引用

2024 ieee/ACS 21st international conference on Computer systems and Applications, AICCSA 2024

作者： Nguyen, Tran Thanh Lam Carminati, Barbara Ferrari, Elena University of Insubria Varese Italy

ISBN: (纸本)9798331518240

Although modern smartphone platforms emphasize user privacy protection by continually improving security mechanisms, vulnerabilities still exist, especially in the case of the Android operating system. The Android security mechanism almost delegates the entire responsibility of granting access permissions to apps to end users, who often are unaware of all the possible consequences of granting permission. Additionally, the loose protection mechanism regulating access to media files (images, videos, audio, etc.) can be exploited by attackers as a side-channel to gather sensitive data. This paper shows how sharing images containing sensitive metadata may result in an intentional or unintentional leakage of users' personal or confidential information. We designed MetaLeak, a system based on apps' hybrid analysis, to assess the identified risks. We used MetaLeak to analyze 5,000 popular apps and found that 21.9% of them sent at least one type of sensitive metadata over the internet. Moreover, for only 10.4% of the apps in our dataset, the app's actual behavior w.r.t. collecting GPS data is compliant with the developer's claims. © 2024 ieee.

关键词： Information leakage

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Network Performance Analysis of Starlink: A Proliferated Low Earth Orbit Satellite internet System 17

Network Performance Analysis of Starlink: A Proliferated Low...

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17th international conference on signal Processing and Communication systems, ICSPCS 2024

作者： Wong, Aaron Buhl, Victor McEachen, John Kennedy, Sean McEachen, James Naval Postgraduate School Electrical and Computer Engineering Monterey United States U.S. Air Force DaytonOH United States

ISBN: (纸本)9798350389630

This paper presents a comprehensive analysis of the network performance of a proliferated Low Earth Orbit (LEO) satellite internet system, specifically the Starlink constellation. Starlink is known for its global internet access via numerous satellites. Our initial interest was in the number of satellites in view of our own terminal. We used deterministic and analytical methods for calculating the number of Starlink satellites over-head revealing a bimodal distribution with respect to latitude centered around the equator. Over a two-week evaluation, we observed significant variability in system throughput, attributed to factors beyond packet loss during satellite handover. We proceeded to examine the routing of network packets through the Starlink network, from California, Hawaii, and the Common-wealth of the Northern Mariana Islands (CNMI), by examining traceroute results to 155 global locations. Results show all internet routes pass through the same Point of Presence (PoP), regardless of destination, until terminals move beyond a satellite's radio horizon. Additionally, round-trip time analysis indicates packets remain in the satellite network in space until nearing the PoP as opposed to coming to ground immediately and transiting via fiber to the PoP. Our findings suggest that satellite count does not correlate with performance, emphasizing the need for improved terrestrial infrastructure. © 2024 ieee.

关键词： Satellite ground stations

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Investigation on BPSK Modulated LoRaWAN for Data Rate Enhancement 3

Investigation on BPSK Modulated LoRaWAN for Data Rate Enhanc...

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3rd ieee international conference on Applied Electromagnetics, signal Processing, and Communication, AESPC 2023

作者： Divyasree, K. Manoj, G. Mansi, A. Sindhukavi, S. Ramesh, Parameswaran Bino, J. Shabana Parveen, M. Bhuvaneswari, P.T.V. Anna University Department of Electronics Engineering Madras Institute of Technology Chennai India St Josephs's Institute of Technology Anna University Department of Electronics and Communication Engineering Chennai India Sri Sairam Engineering College Anna University Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798350358742

The internet of Things (IoT) is an upcoming and promising technology that involves efficient transmission techniques to communicate data obtained from sensory devices in the developed application. The role played by the channel characteristics between these devices is significant, as quality of service metrics are vital factors in determining the performance of the application. To support long-distance communication, LoRaWAN technology is being used in most of the IoT-enabled automation systems. It provides a wider coverage area and encodes the information using Chirp Spread Spectrum (CSS). A low data transmission rate is found to be its major limitation. This research investigates the bit error rate (BER) behaviour of LoRa when the sensed data are modulated with BPSK under different signal-to-noise ratio (SNR). The impact of the spreading factor on data rate is also analyzed. From the MATLAB simulation results, it is found that an increase in the spreading factor reduces the data rate and vice versa. Hence, to obtain a better data rate, a lesser spreading factor is suggested. © 2023 ieee.

关键词： internet of things

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A Semantic Communication Method for Intelligent internet of Things based on images 6

A Semantic Communication Method for Intelligent Internet of ...

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6th international conference on Electronics technology, ICET 2023

作者： Wan, Zhiping Liu, Shaojiang Xu, Zhiming Zou, Jiajun Li, Huizhen Guangzhou Xinhua University School of Information and Intelligence Engineering Guangzhou China

ISBN: (纸本)9798350337693

For image processing tasks in intelligent internet of Things (IoT) devices, the traditional method is to upload the raw image data of IoT devices to an edge/cloud server for processing, and then return the processed results to the IoT end. However, this method may cause significant delay problems and affect the real-time performance of IoT devices and application effects for large data tasks. To solve this problem, this paper proposes an image semantic communication method that reduces the amount of data transmitted by using a semantic encoder to extract key category information and spatial arrangement information from the original image. At the receiving end, key information is regenerated through semantic deconstruction and reconstruction methods using a decoder, so that the receiving end can use the generated image data to perform tasks normally. Simulation results show that this method outperforms traditional communication methods in terms of improving latency performance. © 2023 ieee.

关键词： Semantics

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An Application of Quantum Mechanics to Attention Methods in Computer Vision 48

An Application of Quantum Mechanics to Attention Methods in ...

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48th ieee international conference on Acoustics, Speech and signal Processing, ICASSP 2023

作者： Zhang, Juntao Luo, Yihao Cheng, Peng Li, Zehan Wu, Hao Yu, Kun An, Wenbo Zhou, Jun Ams Institute of System Engineering Beijing China Yichang Testing Technique R&d Institute Yichang China Coolanyp L.L.C. Wuxi China University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9781728163277

This work proposes the quantum-state-based mapping (QSM) for machine learning. QSM uses wave functions that describe microscopic particle systems as mappings. By QSM, original inputs or features extracted by neural networks are processed as quantum states to train wave function parameters. QSM has a low computational cost, almost no additional parameters, and is easy to integrate with other modules. We demonstrate the simplest form of the wave function as a mapping, that is, when a one-dimensional particle is in an infinitely deep potential well, in combination with advanced attention modules. Experiments show that QSM significantly improves the feature recalibration ability of attention module in transfer learning tasks. Then, we tried to analyze the effectiveness of QSM. This work indicates that QSM has an important application value in interdisciplinary machine learning. © 2023 ieee.

关键词： Attention method image classification Quantum mechanics Transfer Learning

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Making Adversarial Attack Imperceptible in Frequency Domain: A Watermark-based Framework

Making Adversarial Attack Imperceptible in Frequency Domain:...

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ieee international conference on Multimedia and Expo (ICME)

作者： Zhang, Hanxiu Cao, Guitao Zhang, Xinyue Xiang, Jing Wu, Chunwei Shanghai Key Lab Trustworthy Comp Shanghai Peoples R China East China Normal Univ MoE Engn Res Ctr SW HW Co Design Technol & Applicat Shanghai 200062 Peoples R China

ISBN: (纸本)9781665468916

With the development of multimedia communication technology, the image information stored in electronic devices faces increasing privacy risks and requires processing for protection. However, it is found that adversarial perturbations added to images for semantic information protection may corrupt the frequency domain watermarks added for copyright statement. With such challenges, we propose an Adversarial Frequency domain Watermarking (AFW) framework to protect images from both copyright and semantic content. Specifically, the AFW framework constructs the images as adversarial examples by embedding crafted adversarial watermarks in the frequency domain, followed by an optimization algorithm to improve the visual quality. Notably, AFW can generally integrate with existing watermark and attack methods. Extensive experiments on five network models and the imageNet dataset demonstrate that the AFW framework can achieve information hiding and adversarial attacking goals under visual quality assurance.

关键词： Digital watermark Adversarial example Frequency domain image security

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