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检索条件"主题词=variational autoencoder"
1532 条 记 录,以下是1331-1340 订阅
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Synthesis of Synthetic Hyperspectral Images with Controllable Spectral Variability Using a Generative Adversarial Network
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REMOTE SENSING 2023年 第16期15卷 3919-3919页
作者: Palsson, Burkni Ulfarsson, Magnus O. Sveinsson, Johannes R. Univ Iceland Fac Elect & Comp Engn IS-105 Reykjavik Iceland
In hyperspectral unmixing (HU), spectral variability in hyperspectral images (HSIs) is a major challenge which has received a lot of attention over the last few years. Here, we propose a method utilizing a generative ... 详细信息
来源: 评论
variational data augmentation for a learning-based granular predictive model of
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ELECTRIC POWER SYSTEMS RESEARCH 2024年 232卷
作者: Zhao, Tianqiao Yue, Meng Jensen, Michael Endo, Satoshi Marschilok, Amy C. Nugent, Brian Cerruti, Brian Spanos, Constantine Brookhaven Natl Lab Upton NY 11973 USA Orange & Rockland Util Inc Pearl River NY 10965 USA Con Edison Co New York NY USA
As the trend in climate change continues, extreme weather events are expected to occur with increasing frequency and severity and pose a significant threat to the electric power infrastructure. Regardless of the effor... 详细信息
来源: 评论
An automatic classification framework for identifying type of plant leaf diseases using multi-scale feature fusion-based adaptive deep network
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BIOMEDICAL SIGNAL PROCESSING AND CONTROL 2024年 第PartA期95卷
作者: Nagachandrika, Bathula Prasath, R. Joe, I. R. Praveen KCG Coll Technol Dept Comp Sci & Engn Chennai 600097 Tamil Nadu India Vellore Inst Technol Comp Sci & Engn Tiruvalam Rd Vellore 632014 Tamil Nadu India
This method of identifying plant leaf disease generally involves a large team of experts with extensive knowledge of plant diseases, and it can be expensive, time-consuming, and subjective. Hence, a novel plant leaf d... 详细信息
来源: 评论
Online training of deep neural networks for classification
Online training of deep neural networks for classification
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作者: Tumpach, Jiří Charles University of Prague
Deep learning is usually applied to static datasets. If used for classification based on data streams, it is not easy to take into account a non-stationarity. This thesis presents work in progress on a new method for ... 详细信息
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Energy Theft Detection Model Based on VAE-GAN for Imbalanced Dataset
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ENERGIES 2023年 第3期16卷 1109-1109页
作者: Sun, Youngghyu Lee, Jiyoung Kim, Soohyun Seon, Joonho Lee, Seongwoo Kyeong, Chanuk Kim, Jinyoung Kwangwoon Univ Dept Elect Convergence Engn Seoul 01897 South Korea
Energy theft causes a lot of economic losses every year. In the practical environment of energy theft detection, it is required to solve imbalanced data problem where normal user data are significantly larger than ene... 详细信息
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Open-set lung sound recognition model based on conditional Gaussian capsule network and variational time-frequency feature reconstruction
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BIOMEDICAL SIGNAL PROCESSING AND CONTROL 2024年 第PartB期87卷
作者: Zhang, Yixuan Zhang, Jingye Shi, Lukui Hebei Univ Technol Sch Artificial Intelligence Tianjin 300401 Peoples R China
Lung sound auscultation is an essential method for diagnosing lung diseases;however, most existing lung sound recognition methods fail to identify classes that are unknown in training. Thus, we proposed an open-set lu... 详细信息
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Deep learning methods for forecasting COVID-19 time-Series data: A Comparative study
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CHAOS SOLITONS & FRACTALS 2020年 140卷 110121-110121页
作者: Zeroual, Abdelhafid Harrou, Fouzi Dairi, Abdelkader Sun, Ying Univ 20 August 1955 Fac Technol Dept Elect Engn Skikda 21000 Algeria Univ 08 May 1945 LAIG Lab Guelma 24000 Algeria King Abdullah Univ Sci & Technol KAUST Comp Elect & Math Sci & Engn CEMSE Div Thuwal 239556900 Saudi Arabia Univ Sci & Technol Oran Mohamed Boudiaf USTO MB Comp Sci Dept Signal Image & Speech Lab SIMPA Lab BP 1505 Bir El Djir 31000 Oran Algeria
The novel coronavirus (COVID-19) has significantly spread over the world and comes up with new challenges to the research community. Although governments imposing numerous containment and social distancing measures, t... 详细信息
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variational transformer-based anomaly detection approach for multivariate time series
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MEASUREMENT 2022年 191卷 110791-110791页
作者: Wang, Xixuan Pi, Dechang Zhang, Xiangyan Liu, Hao Guo, Chang Nanjing Univ Aeronaut & Astronaut Coll Comp Sci & Technol Nanjing Jiangsu Peoples R China Beijing Inst Spacecraft Syst Engn Beijing Peoples R China
Due to the strategic importance of satellites, the safety and reliability of satellites have become more important. Sensors that monitor satellites generate lots of multivariate time series, and the abnormal patterns ... 详细信息
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Latent Out: an unsupervised deep anomaly detection approach exploiting latent space distribution
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MACHINE LEARNING 2023年 第11期112卷 4323-4349页
作者: Angiulli, Fabrizio Fassetti, Fabio Ferragina, Luca Univ Calabria DIMES I-87036 Arcavacata Di Rende Italy
Anomaly detection methods exploiting autoencoders (AE) have shown good performances. Unfortunately, deep non-linear architectures are able to perform high dimensionality reduction while keeping reconstruction error lo... 详细信息
来源: 评论
variational co-embedding learning for attributed network clustering
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KNOWLEDGE-BASED SYSTEMS 2023年 第1期270卷
作者: Yang, Shuiqiao Verma, Sunny Cai, Borui Jiang, Jiaojiao Yu, Kun Chen, Fang Yu, Shui Univ New South Wales Sch Comp Sci & Engn Sydney NSW 2052 Australia Deakin Univ Sch Informat Technol Burwood Vic 3125 Australia Macquarie Univ Sch Engn Macquarie Pk NSW 2109 Australia Univ Technol Sydney Data Sci Inst Ultimo NSW 2007 Australia Univ Technol Sydney Sch Comp Sci Ultimo NSW 2007 Australia
Recent developments in attributed network clustering combine graph neural networks and autoencoders for unsupervised learning. Although effective, these techniques suffer from either (a) clustering-unfriendly embeddin... 详细信息
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