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检索条件"机构=Center of Signal and Image Processing School of Electrical and Computer Engineering"
413 条 记 录,以下是51-60 订阅
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Real-Time Fault Detection Scheme for Industrial Chemical Tennessee Eastman Process
Real-Time Fault Detection Scheme for Industrial Chemical Ten...
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International Conference on Control, Decision and Information Technologies (CoDIT)
作者: Khadija Attouri Majdi Mansouri Mansour Hajji Abdelmalek Kouadri Kais Bouzrara Hazem Nounou Institut Superieur des Sciences Appliques et de Technologie de Kasserine Kairouan University Tunisia The Department of Electrical and Computer Engineering Program Texas A&M University at Qatar Doha Qatar Signals and Systems Laboratory Institute of Electrical and Electronics Engineering University M Hamed Bougara of Boumerdes Boumerdes Algeria The Research Laboratory of Automation Signal Processing and Image National Engineering School of Monastir Tunisia
The key idea behind this study is to integrate a moving window dynamic PCA (MW-DPCA) methodology for fault detection within the Tennessee Eastman process (TEP) into a low-computational power system, the Raspberry Pi 4... 详细信息
来源: 评论
Geometrically Inspired Kernel Machines for Collaborative Learning Beyond Gradient Descent
arXiv
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arXiv 2024年
作者: Kumar, Mohit Valentinitsch, Alexander Fuchs, Magdalena Brucker, Mathias Bowles, Juliana Husakovic, Adnan Abbas, Ali Moser, Bernhard A. Faculty of Computer Science and Electrical Engineering University of Rostock Germany Software Competence Center Hagenberg GmbH HagenbergA-4232 Austria School of Computer Science University of St Andrews United Kingdom Primetals Technologies Austria GmbH LinzA-4031 Austria Institute of Signal Processing Johannes Kepler University Linz Austria
This paper develops a novel mathematical framework for collaborative learning by means of geometrically inspired kernel machines which includes statements on the bounds of generalisation and approximation errors, and ... 详细信息
来源: 评论
Iterative Random Training Sampling Convolutional Neural Network for Hyperspectral image Classification
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IEEE Transactions on Geoscience and Remote Sensing 2023年 61卷
作者: Chang, Chein-I Liang, Chia-Chen Hu, Peter Fuming University of Maryland Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering BaltimoreMD21250 United States National Cheng Kung University Department of Electrical Engineering Tainan70101 Taiwan Providence University Department of Computer Science and Information Management Taichung02912 Taiwan University of Maryland School of Medicine R. A. Cowley Shock Trauma Center Shock Trauma Anesthesia Organized Research Center Department of Anesthesia BaltimoreMD21201 United States
Convolutional neural network (CNN) has received considerable interest in hyperspectral image classification (HSIC) lately due to its excellent spectral-spatial feature extraction capability. To improve CNN, many appro... 详细信息
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CrackCLF: Automatic Pavement Crack Detection based on Closed-Loop Feedback
arXiv
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arXiv 2023年
作者: Li, Chong Fan, Zhun Chen, Ying Lin, Huibiao Moretti, Laura Loprencipe, Giuseppe Sheng, Weihua Wang, Kelvin C.P. The Key Lab of Digital Signal and Image Processing of Guangdong Province College of Engineering Shantou University Shantou515063 China The Department of Civil Construction and Environmental Engineering Sapienza University of Rome Rome00184 Italy The School of Electrical and Computer Engineering Oklahoma State University StillwaterOK74078 United States The School of Civil and Environmental Engineering Oklahoma State University StillwaterOK74078 United States
Automatic pavement crack detection is an important task to ensure the functional performances of pavements during their service life. Inspired by deep learning (DL), the encoder-decoder framework is a powerful tool fo... 详细信息
来源: 评论
Efficient Contextformer: Spatio-Channel Window Attention for Fast Context Modeling in Learned image Compression
arXiv
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arXiv 2023年
作者: Burakhan Koyuncu, A. Jia, Panqi Boev, Atanas Alshina, Elena Steinbach, Eckehard The Technical University of Munich School of Computation Information and Technology Department of Computer Engineering Media Technology Munich80333 Germany The Friedrich-Alexander University Department of Electrical-Electronic-Communication Engineering Multimedia Communications and Signal Processing Erlangen91058 Germany The Huawei Munich Research Center Munich80992 Germany
Entropy estimation is essential for the performance of learned image compression. It has been demonstrated that a transformer-based entropy model is of critical importance for achieving a high compression ratio, howev... 详细信息
来源: 评论
Unpaired Overwater image Defogging Using Prior Map Guided Cycle-Consistent Generative Adversarial Network
SSRN
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SSRN 2024年
作者: Mo, Yaozong Li, Chaofeng Ren, Wenqi Wang, Wenwu Wu, Xiao-Jun Shanghai201306 China School of Cyber Science and Technology Sun Yat-sen University Shenzhen518000 China Center for Vision Speech and Signal Processing Department of Electrical and Electronic Engineering University of Surrey Surrey SurreyGU2 7XH United Kingdom School of Artificial Intelligence and Computer Science Jiangnan University Wuxi 214122 China
Existing image defogging approaches have made significant advancements. But their effectiveness in addressing overwater foggy images remains limited. Current methods are predominantly optimized for land scenes, which ... 详细信息
来源: 评论
Multi-modal signal integration for enhanced sleep stage classification: Leveraging EOG and 2-channel EEG data with advanced feature extraction
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Artificial Intelligence in Medicine 2025年 166卷 103152-103152页
作者: Samaee, Mahdi Yazdi, Mehran Massicotte, Daniel Signal and Image Processing Laboratory School of Electrical and Computer Engineering Shiraz University Shiraz Iran Laboratory of Signal and System Integration Department of Electrical and Computer Engineering Université du Québec à Trois-Rivières Trois-Rivières Canada
This paper introduces an innovative approach to sleep stage classification, leveraging a multi-modal signal integration framework encompassing Electrooculography (EOG) and two-channel electroencephalography (EEG) data... 详细信息
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An Insight Into Neurodegeneration: Harnessing Functional MRI Connectivity in the Diagnosis of Mild Cognitive Impairment
An Insight Into Neurodegeneration: Harnessing Functional MRI...
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17th International Joint Conference on Biomedical engineering Systems and Technologies, BIOSTEC 2024
作者: Han, Shuning Sun, Zhe Zhao, Kanhao Duan, Feng Caiafa, Cesar F. Zhang, Yu Solé-Casals, Jordi Data and Signal Processing Research Group University of Vic-Central University of Catalonia Catalonia Vic08500 Spain Image Processing Research Group RIKEN Center for Advanced Photonics Riken Saitama Wako-Shi Japan Faculty of Health Data Science Juntendo University Chiba Urayasu Japan Department of Bioengineering Lehigh University BethlehemPA18015 United States Tianjin Key Laboratory of Brain Science and Intelligent Rehabilitation Nankai University Tianjin China Instituto Argentino de Radioastronomía-CCT La Plata CONICET/ CIC-PBA/ UNLP V. Elisa 1894 Argentina Department of Electrical and Computer Engineering Lehigh University BethlehemPA18015 United States Department of Psychiatry University of Cambridge CambridgeCB20SZ United Kingdom
Alzheimer’s disease is a progressive form of memory loss that worsens over time. Detecting it early, when memory issues are mild, is crucial for effective interventions. Recent advancements in computer technology, sp... 详细信息
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Epileptic Seizure Detection Using a Hybrid 1D CNN-Machine Learning Approach from EEG Data
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Journal of Healthcare engineering 2022年 第1期2022卷 9579422页
作者: Hassan, Fatima Hussain, Syed Fawad Qaisar, Saeed Mian Faculty of Computer Science and Engineering G. I. K. Institute Topi Pakistan School of Computer Science University of Birmingham Birmingham United Kingdom Electrical and Computer Engineering Department Effat University Jeddah22332 Saudi Arabia Communication and Signal Processing Lab Energy and Technology Research Center Effat University Jeddah22332 Saudi Arabia
Electroencephalography (EEG) is a widely used technique for the detection of epileptic seizures. It can be recorded in a noninvasive manner to present the electrical activity of the brain. The visual inspection of non... 详细信息
来源: 评论
AI-enabled CT-guided end-to-end quantification of total cardiac activity in 18FDG cardiac PET/CT for detection of cardiac sarcoidosis
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Journal of Nuclear Cardiology 2025年 48卷 102195页
作者: Miller, Robert JH. Shanbhag, Aakash Marcinkiewicz, Anna M. Struble, Helen Gransar, Heidi Hijazi, Waseem Fujito, Hidesato Kransdorf, Evan Kavanagh, Paul Liang, Joanna X. Builoff, Valerie Dey, Damini Berman, Daniel S. Slomka, Piotr J. Departments of Medicine (Division of Artificial Intelligence in Medicine) Imaging and Biomedical Sciences Cedars-Sinai Medical Center Los Angeles CA United States Department of Cardiac Sciences University of Calgary Calgary AB Canada Signal and Image Processing Institute Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los Angeles CA United States Center of Radiological Diagnostics National Medical Institute of the Ministry of the Interior and Administration Warsaw Poland
Background: [18F]-fluorodeoxyglucose ([18F]FDG) positron emission tomography (PET) plays a central role in diagnosing and managing cardiac sarcoidosis. We propose a fully automated pipeline for quantification of [18F]... 详细信息
来源: 评论