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

共 6141 条记录，以下是31-40 订阅

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international conference on signal image technology and internet based systems

International Conference on Signal Image Technology and Inte...

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3rd IEEE international conference on signal image Technologies and internet based systems, sitis'07

ISBN: (纸本)9780769531229

The proceedings contain 141 papers. The topics discussed include: improve image annotation by combining multiple models;a semantic framework for spatiotemporal data representation;a methodology for low-cost image annotation based on conceptual modeling: a biological example;extraction of ambiguous sequential patterns with least minimum generalization for mismatch clusters;distributed frequent closed itemsets mining;effective site customization based on Web semantics and usage mining;an adaptive privacy preserving data mining model under distributed environment;linguistic analysis of users' queries: towards an adaptive information retrieval system;an analysis of constructed categories for for textual classification using fuzzy similarity and agglomerative hierarchical methods;and optimization algorithm and data security problem in distributed information systems.

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Application of Smart Terminals in the Power Industrial internet

Application of Smart Terminals in the Power Industrial Inter...

引用

international Hydropower Development conference, IHDC 2024

作者： Fuqiang, Huang Zhengpu, Chen Jiangtao, Xiao Zhaoan, Jin Jun, Chen Hai, Yang Xiluodu Hydropower Station China Yangtze Power Co. Ltd. Yunnan Province Yongshan County657300 China State Grid International Development Co. Ltd. Hong Kong Shanghai Liqian Power Technology Co. Ltd. Shenzhen China College of Electrical Engineering and Control Science Nanjing Tech University Nanjing China

ISBN: (纸本)9789819791835

The Power Industrial internet serves as an essential platform for the digital transformation of the electric power industry, during its implementation, the integration of Information technology (IT) and Operational technology (OT) in power production and maintenance has posed significant challenges, necessitating the development of intelligent equipment based on Cyber-Physical systems (CPS) to bridge this gap. Microcomputer platforms are well-established and reliable systems capable of running various complex algorithms. However, traditional microcomputer-based protection devices face limitations such as firmware programming, limited types of signal sampling, and insufficient data transmission capabilities. In the current era of digital transformation, there is an urgent need for intelligent devices and smart terminals that can overcome these shortcomings through cloud-edge collaboration to assist the digital transformation of the power industry, continuously creating effective applications that enhance quality and efficiency, and fostering new productive forces. This article starts from the strategic orientation of industrial development, the problem orientation of digital transformation, and the demand orientation for quality improvement and efficiency enhancement. It focuses on the key issues in the advancement of the industrial internet, proposes solutions based on microcomputer platforms, and explores new directions in the development of intelligent and digital transformation in the field of relay protection specialization. © The Author(s) 2025.

关键词： Cloud-Edge Collaboration Cyber-Physical systems Industrial internet Microcomputer Platform Power Industry Smart Terminal

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Hand Gesture Recognition Method based on mmWave Radar with MobileViT and Knowledge Distillation 16

Hand Gesture Recognition Method based on mmWave Radar with M...

引用

16th international conference on signal Processing systems, ICSPS 2024

作者： Zhang, Xiangqun Ge, Zhizhou Lu, Kai Du, Genyuan Shen, Jiawen Gao, Xiangqian School of Information Engineering Xuchang University Xuchang461000 China Henan International Joint Laboratory of Polarization Sensing and Intelligent Signal Processing Xuchang461000 China Henan Shengshi Hengxin Technology Co. Ltd Xuchang461111 China

ISBN: (纸本)9781510689251

Human-hand gesture recognition using millimetre wave radar is attractive in human-computer interfaces, industrial internet of Things, and smart home. However, the existing CNN or RNN model is so complex and large that it is hard to apply to mobile vision tasks and embedded devices. This paper proposes dual lightweight convolutional neural networks, MobileViT and knowledge distillation, to solve this problem. Firstly, we acquire the original radar echoes of frequency-modulated continuous wave (FWCW) signal and reshape the three-dimensional matrix by Chirps * Samples * Frames. Then, we perform the signal processing method to eliminate the noise and static background. Secondly, we employ the Fast Fourier Transform to extract the hand gestures feature map of distance and Doppler information. Finally, the feature map is input into the modified MobileViT to recognize dynamic hand gestures, and knowledge distillation models is used to simplify the model structure. The experimental results show that the parameter space complexity of the constructed model is reduced to 0.018 M, and the computational complexity is 0.082 GFLOPs after knowledge distillation *** method is verified in 12 complex gesture. It has the potential to be applied in mobile tasks and embedded devices. © 2025 SPIE.

关键词： Fast Fourier transforms

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Enhanced Edge Attention-based SRCNN for Retinal image Super-Resolution 1

Enhanced Edge Attention-Based SRCNN for Retinal Image Super-...

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1st international conference on Intelligent systems and Computational Networks, ICISCN 2025

作者： Koshika, Manoj Kandukuri, Prabhakar Moppey, Shyam Kumar Chaitanya Bharathi Institute of Technology Department of Artificial Intelligence & Machine Learning Gandipet Hyderabad India

ISBN: (纸本)9798331529246

The early recognition of retinal disorders such as cataracts, glaucoma, and retinal problems is highly dependent on high-resolution retinal imaging, which is a complex issue because of poor image quality and the lack of important features. The proposed Enhanced Edge Attention Super Resolution Convolutional Neural Network (EEASRCNN) is designed to improve the quality of retinal images high precisely. The model preserves important details like blood vessels and the optic disc by using a custom edge loss function, sharpening filters, and combined attention mechanisms. With a high structural similarity index (SSIM) and peak signal-to-noise ratio (PSNR) score and an accuracy of 97.16% in preserving structural details, EEASRCNN outperforms traditional super-resolution methods after being trained on a dataset of diverse retinal images. EEASRCNN offers effective image super resolution in real-time medical image diagnosis. © 2025 IEEE.

关键词： Ophthalmology

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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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Detection Method for Loose Points in Transformer Iron Cores based on MTF and CNN

Detection Method for Loose Points in Transformer Iron Cores ...

引用

international conference of Electrical, Electronic and Networked Energy systems, EENES 2024

作者： Xu, Weijie Ding, De Zhang, Changgeng Environmental Protection Technique Center Co. Limited Shaanxi China Hebei University of Technology Tianjin China

ISBN: (纸本)9789819618552

The vibration signal of the transformer core is closely related to its mechanical state, and exploiting this characteristic enables the detection of loosening points in the transformer core. This paper proposes a method for detecting loosening points in the transformer core based on Markov Transition Field (MTF) and Convolutional Neural Network (CNN). Firstly, the initial vibration signal of the transformer core is decomposed using Ensemble Empirical Mode Decomposition (EEMD), and suitable components are selected for signal reconstruction to eliminate interference from the transformer itself and the external environment. Subsequently, the reconstructed signal’s MTF image is obtained through MTF transformation. Finally, the MTF image is utilized as the input for CNN to accomplish the detection of loosening points in the transformer core. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Markov processes

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Explaining Representations in Correlation-based Deep Multiview Representation Learning

Explaining Representations in Correlation-based Deep Multivi...

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2025 IEEE international conference on Acoustics, Speech, and signal Processing, ICASSP 2025

作者： Kuschel, Maurice Alkhatib, Amr Hasija, Tanuj Boström, Henrik Signal and System Theory Group Paderborn University Paderborn Germany Division of Software and Computer Systems KTH Royal Institue of Technology Stockholm Sweden

ISBN: (纸本)9798350368741

Multiview representation learning techniques based on deep correlation maximization have become increasingly popular for learning meaningful and compact representations from multiview data. Even though their performance is state-of-the-art in many interpretability-critical fields, their black-box behavior poses a problem and restricts their usability. To overcome this restriction, we propose XDCCA (eXplanations for Deep Canonical Correlation Analysis), an explanation strategy using characteristic rules in combination with SHAP that exploits the inherent structure of latent spaces created by correlation maximization techniques. We demonstrate how XDCCA allows for interpreting learned representations and their correlation using real medical time series and synthetic image data. © 2025 IEEE.

关键词： CEGA Deep Canonical Correlation Analysis Explainable AI Multiview Representation Learning SHAP

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A Grouping Strategy-based Progressive Fusion Network for Hyperspectral image Super-Resolution

A Grouping Strategy-Based Progressive Fusion Network for Hyp...

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2025 IEEE international conference on Acoustics, Speech, and signal Processing, ICASSP 2025

作者： Lv, Guohua Zhang, Baodong Gao, Yongbiao Zhao, Guixin Wang, Guotao Wang, Juncan Jinan China Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing Shandong Fundamental Research Center for Computer Science Jinan China Shandong Key Laboratory of Ubiquitous Intelligent Computing Jinan China Ministry of Education China Beihang University Beijing China

ISBN: (纸本)9798350368741

Hyperspectral super-resolution involves combining low-resolution hyperspectral images with high-resolution multispectral images to produce a high-resolution hyperspectral image. Recently, although many methods for hyperspectral image super-resolution have been proposed, they often fail to fully utilize the high similarity among adjacent bands to enhance fusion performance. Therefore, we propose a grouping strategy-based progressive fusion network (GPFNet) for hyperspectral super-resolution. The core of GPFNet is the grouping strategy fusion block (GPF block), in which grouping-based spatial-spectral information fusion and spatial information refinement are performed. We design the spatial-spectral information fusion module (SSIFM) based on grouped convolutions to capture the feature differences from adjacent bands. To refine spatial details, we develop the spatial information enhancement module (SpaEM), which leverages the hierarchical features extracted by the multi-scale feature extraction module (MIEM). Additionally, a progressive fusion strategy, which involves using multiple upsampled hyperspectral images and downsampled multispectral images, further preserves spectral integrity and spatial details. Extensive experiments show that GPFNet outperforms state-of-the-art methods both qualitatively and quantitatively. © 2025 IEEE.

关键词： group convolution Hyperspectral image image fusion super-resolution

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Research on high accuracy classification of temperature signals based on OFDR technology and EfficientNet 4

Research on high accuracy classification of temperature sign...

引用

4th international conference on Advanced Manufacturing technology and Electronic Information, AMTEI 2024

作者： Shang, Chuanyin Li, Peng Tong, Zhengrong Wang, Hao Li, Sibo Tianjin Key Laboratory of Thin Film Electronics and Communication Devices Engineering Research Center for Optoelectronic Devices and Communication Technology the Ministry of Education School of Integrated Circuit Science and Engineering Tianjin University of Technology Tianjin300384 China

ISBN: (数字)9781510688247

ISBN: (纸本)9781510688230

The development of machine learning is driving revolutionary changes and unprecedented opportunities across various industries. This paper introduces a new temperature monitoring method that combines the efficient deep learning model EfficientNet with Optical Frequency Domain Reflectometry (OFDR). We utilize distributed fiber-optic sensing technology based on OFDR to collect one-dimensional temperature signals under different temperature conditions, which we then transform into a two-dimensional image format suitable for machine learning processing. The dataset is subsequently trained using the EfficientNet deep learning model. The results show that the trained model achieves a high accuracy rate of 97.5% on the test dataset. This research not only demonstrates the feasibility of efficiently and accurately monitoring temperature changes but also provides new solutions and technological pathways for areas such as environmental monitoring, industrial automation, and safety systems. © 2025 SPIE.

关键词： Education and training Data modeling Performance modeling Fiber optics sensors Machine learning Matrices Fiber optics image processing Reliability signal processing

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Quantum image encryption algorithm based on generalized Arnold transform and Lorenz chaotic systems

Quantum image encryption algorithm based on generalized Arno...

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2024 international conference Optoelectronic Information and Optical Engineering, OIOE 2024

作者： Zhang, Ruqing School of Information Engineering Shanghai Maritime University Shanghai201306 China

ISBN: (数字)9781510688209

ISBN: (纸本)9781510688193

With the rapid development of the internet and information technology, the traditional encryption methods suffer from drawbacks such as poor processing capacity and low security, making them vulnerable to attacks. This paper presents a hybrid encryption algorithm that combines the Lorenz chaotic system and the generalized Arnold transform to enhance information security and confidentiality in digital images. The proposed quantum encryption scheme involves two stages: interfering with pixel coordinate information and grayscale values using the generalized Arnold transform, followed by spatial domain scrambling of pixel positions using the Lorenz chaotic system. MATLAB simulations demonstrate the effectiveness of this algorithm in achieving the desired confusion and diffusion of pixel values, making it a superior encryption method for cryptography. © 2025 SPIE.

关键词： Encryption algorithms

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