Results 21 to 30 of about 60,311 (308)
Anomaly Detection for Agricultural Vehicles Using Autoencoders
Sensors, 2022 The safe in-field operation of autonomous agricultural vehicles requires detecting all objects that pose a risk of collision. Current vision-based algorithms for object detection and classification are unable to detect unknown classes of objects. In this
Esma Mujkic +4 more
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Review on autoencoder and its application
Tongxin xuebao, 2021 As a typical deep unsupervised learning model, autoencoder can automatically learn effective abstract features from unlabeled samples.In recent years, autoencoder has been widely used in target recognition, intrusion detection, fault diagnosis and many ...
Jie LAI +4 more
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Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, 2023 This paper presents a new hybrid algorithm using multiple Support Vector Machines models with convolutional autoencoder to Electrical Impedance Tomography, and Ultrasound Computed Tomography image reconstruction.
Łukasz Maciura +3 more
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Biological Cybernetics, 2022 AbstractIn Bourlard and Kamp (Biol Cybern 59(4):291–294, 1998), it was theoretically proven that autoencoders (AE) with single hidden layer (previously called “auto-associative multilayer perceptrons”) were, in the best case, implementing singular value decomposition (SVD) Golub and Reinsch (Linear algebra, Singular value decomposition and least ...
Hervé Bourlard, Selen Hande Kabil
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Energy Reports, 2021 Anomaly detection for hydropower turbine unit is a requirement for the safety of hydropower system. An unsupervised anomaly detection method employing variational modal decomposition (VMD) and deep autoencoder is proposed.
Hongteng Wang +3 more
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, 2023 (a) Diagram of the autoencoder components (b) Original spike and the reconstruction made by an autoencoder.
Ana-Maria Ichim (14648702) +4 more
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Autoencoder-based characterization of QCD multijet background at the LHC [PDF]
, 2023 openA proof of principle for the application of autoencoders in encoding high-dimensional multijet data is presented. A simulation with events containing four b-quark QCD jets is used to train the autoencoder. The reconstruction of events after a reduced
MARIÑO VILLADAMIGO, JAVIER
core
CoRR, 2023 Synthetic data generation is increasingly important due to privacy concerns. While Autoencoder-based approaches have been widely used for this purpose, sampling from their latent spaces can be challenging. Mixture models are currently the most efficient way to sample from these spaces.
Aymene Mohammed Bouayed, David Naccache
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Unsupervised Outlier Detection via Transformation Invariant Autoencoder
IEEE Access, 2021 Autoencoder based methods are the majority of deep unsupervised outlier detection methods. However, these methods perform not well on complex image datasets and suffer from the noise introduced by outliers, especially when the outlier ratio is high.
Zhen Cheng +4 more
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