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检索条件"主题词=Autoencoder"
4258 条 记 录,以下是451-460 订阅
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A shallow network for hyperspectral image classification using an autoencoder with convolutional neural network
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MULTIMEDIA TOOLS AND APPLICATIONS 2022年 第1期81卷 695-714页
作者: Patel, Heena Upla, Kishor P. Sardar Vallabhbhai Natl Inst Technol Surat 395007 India
This paper addresses an approach for the classification of hyperspectral imagery (HSI). In remote sensing, the HSI sensor acquires hundreds of images with narrow and continuous spectral width in visible and near-infra... 详细信息
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Representation learning of 3D meshes using an autoencoder in the spectral domain
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COMPUTERS & GRAPHICS-UK 2022年 107卷 131-143页
作者: Lemeunier, Clement Denis, Florence Lavoue, Guillaume Dupont, Florent Univ Lyon CNRS INSA Lyon UCBLLIRISUMR5205 F-69622 Villeurbanne France Univ Lyon UCBL CNRS INSA LyonLIRISUMR5205 F-69622 Villeurbanne France Univ Lyon Cent Lyon CNRS INSA LyonUCBLLIRISUMR5205ENISE F-42023 Saint Etienne France
Learning on surfaces is a difficult task: the data being non-Euclidean makes the transfer of known techniques such as convolutions and pooling non trivial. Common methods deploy processes to apply deep learning operat... 详细信息
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Spectral-Spatial Feature Extraction With Dual Graph autoencoder for Hyperspectral Image Clustering
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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2022年 第12期32卷 8500-8511页
作者: Zhang, Yongshan Wang, Yang Chen, Xiaohong Jiang, Xinwei Zhou, Yicong China Univ Geosci Sch Comp Sci Wuhan 430074 Peoples R China China Univ Geosci Hubei Key Lab Intelligent Geoinformat Proc Wuhan 430074 Peoples R China Univ Macau Dept Comp & Informat Sci Taipa Macau Peoples R China
autoencoder (AE) is an unsupervised neural network framework for efficient and effective feature extraction. Most AE-based methods do not consider spatial information and band correlations for hyperspectral image (HSI... 详细信息
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Personalized recommendation with knowledge graph via dual-autoencoder
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APPLIED INTELLIGENCE 2022年 第6期52卷 6196-6207页
作者: Yang, Yang Zhu, Yi Li, Yun Yangzhou Univ Sch Informat Engn Yangzhou 225009 Jiangsu Peoples R China Hefei Univ Technol Key Lab Knowledge Engn Big Data Minist Educ Hefei 230009 Peoples R China Hefei Univ Technol Sch Comp Sci & Informat Engn Hefei 230009 Peoples R China
In the past decades, personalized recommendation systems have attracted a vast amount of attention and researches from multiple disciplines. Recently, for the powerful ability of feature representation learning, deep ... 详细信息
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Estimation of missing air pollutant data using a spatiotemporal convolutional autoencoder (May, 10.1007/s00521-022-07224-2, 2022)
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NEURAL COMPUTING & APPLICATIONS 2022年 第18期34卷 16155-16155页
作者: Wardana, I. Nyoman Kusuma Gardner, Julian W. Fahmy, Suhaib A. Univ Warwick Sch Engn Coventry CV4 7AL W Midlands England King Abdullah Univ Sci & Technol KAUST Comp Elect & Math Sci & Engn Thuwal 23955 Saudi Arabia Politekn Negeri Bali Dept Elect Engn Bali 80364 Indonesia
A key challenge in building machine learning models for time series prediction is the incompleteness of the datasets. Missing data can arise for a variety of reasons, including sensor failure and n... 详细信息
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RffAe-S: autoencoder Based on Random Fourier Feature With Separable Loss for Unsupervised Signal Modulation Clustering
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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2022年 第11期18卷 7910-7919页
作者: Bai, Jing Wang, Yiran Xiao, Zhu Alazab, Mamoun Xidian Univ Sch Artificial Intelligence Key Lab Intelligent Percept & Image Understanding Minist Educ Xian 710071 Peoples R China Guangdong Lab Artificial Intelligence & Digital E Shenzhen 518060 Peoples R China Hunan Univ Coll Comp Sci & Elect Engn Changsha 410082 Peoples R China Charles Darwin Univ Casuarina NT 0811 Australia
Unsupervised signal modulation clustering is becoming increasingly important due to its application in the dynamic spectrum access process of 5G wireless communication and threat detection at the physical layer of Int... 详细信息
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LSTM-autoencoder Deep Learning Technique for PAPR Reduction in Visible Light Communication
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IEEE ACCESS 2022年 10卷 113028-113034页
作者: Mohamed, Abdelfatah Eldien, Adly S. Tag Fouda, Mostafa M. Saad, Reham S. Benha Univ Fac Engn Shoubra Dept Elect Engn Cairo 11672 Egypt Idaho State Univ Coll Sci & Engn Dept Elect & Comp Engn Pocatello ID 83209 USA
Visible light communication (VLC) is a relatively new wireless communication technology that allows for high data rate transfer. Because of its capability to enable high-speed transmission and eliminate inter-symbol i... 详细信息
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Zero-day Ransomware Attack Detection using Deep Contractive autoencoder and Voting based Ensemble Classifier
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APPLIED INTELLIGENCE 2022年 第12期52卷 13941-13960页
作者: Zahoora, Umme Rajarajan, Muttukrishnan Pan, Zahoqing Khan, Asifullah Pakistan Inst Engn & Appl Sci Dept Comp & Informat Sci Islamabad 45650 Pakistan City Univ London Sch Math Comp Sci & Engn London EC1V 0HB England Nanjing Univ Informat Sci & Technol Sch Comp & Software Nanjing 210044 Peoples R China Pakistan Inst Engn & Appl Sci Ctr Math Sci Islamabad 45650 Pakistan Pakistan Inst Engn & Appl Sci PIEAS Artificial Intelligence Ctr PAIC Islamabad 45650 Pakistan
Ransomware attacks are hazardous cyber-attacks that use cryptographic methods to hold victims' data until the ransom is paid. Zero-day ransomware attacks try to exploit new vulnerabilities and are considered a sev... 详细信息
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Constrained autoencoder-Based Pulse Compressed Thermal Wave Imaging for Sub-Surface Defect Detection
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IEEE SENSORS JOURNAL 2022年 第18期22卷 17335-17342页
作者: Kaur, Kirandeep Mulaveesala, Ravibabu Mishra, Priyanka Indian Inst Technol Ropar Dept Elect Engn Infrared Imaging Lab Rupnagar 140001 India
Non-destructive testing & evaluation techniques play an essential role in ensuring safety of materials in operation at various industry sectors. Pulse compressed favourable thermal wave imaging is one of the widel... 详细信息
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Stock market network based on bi-dimensional histogram and autoencoder
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INTELLIGENT DATA ANALYSIS 2022年 第3期26卷 723-750页
作者: Choi, Sungyoon Gwak, Dongkyu Song, Jae Wook Chang, Woojin Seoul Natl Univ Dept Ind Engn Seoul 08826 South Korea Hanyang Univ Dept Ind Engn Seoul South Korea Seoul Natl Univ Inst Ind Syst Innovat Seoul South Korea Seoul Natl Univ SNU Inst Res Finance & Econ Seoul South Korea
In this study, we propose a deep learning related framework to analyze S&P500 stocks using bi-dimensional histogram and autoencoder. The bi-dimensional histogram consisting of daily returns of stock price and stoc... 详细信息
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