Results 81 to 90 of about 13,513 (170)
SensorsThis paper discusses the problem of recognizing defective epoxy drop images for the purpose of performing vision-based die attachment inspection in integrated circuit (IC) manufacturing based on deep neural networks.
Lamia Alam, Nasser Kehtarnavaz
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A Multi-Level-Denoising Autoencoder Approach for Wind Turbine Fault Detection
IEEE Access, 2019 The effective fault detection of wind turbines (WTs) can greatly help to improve their availability and reduce their operation and maintenance costs. In this context, data-driven fault detection approaches have attracted a lot of interests due to the ...
Xin Wu +4 more
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Journal of Machine Learning for Modeling and ComputingData-driven reduced-order modeling of chaotic dynamics can result in systems that either dissipate or diverge catastrophically. Leveraging nonlinear dimensionality reduction of autoencoders and the freedom of nonlinear operator inference with neural networks, we aim to solve this problem by imposing a synthetic constraint in the reduced-order space ...
Popov, Andrey A., Zanetti, Renato
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The Journal of SupercomputingFeature selection is a fundamental technique for reducing the dimensionality of high-dimensional data by identifying the most relevant features while discarding redundant or irrelevant ones. In unsupervised settings, where labeled data are unavailable and labeling is costly, effective feature selection becomes even more challenging. This paper proposes
Hashemi, Amin +3 more
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A tutorial on multi-view autoencoders using the multi-view-AE library
There has been a growing interest in recent years in modelling multiple modalities (or views) of data to for example, understand the relationship between modalities or to generate missing data. Multi-view autoencoders have gained significant traction for their adaptability and versatility in modelling multi-modal data, demonstrating an ability to ...
Aguila, Ana Lawry, Altmann, Andre
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Ae$$^2$$I: A Double Autoencoder for Imputation of Missing Values
The most common strategy of imputing missing values in a table is to study either the column-column relationship or the row-row relationship of the data table, then use the relationship to impute the missing values based on the non-missing values from other columns of the same row, or from the other rows of the same column.
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AE-ViT: Token Enhancement for Vision Transformers via CNN-Based Autoencoder Ensembles
International Journal of Artificial Intelligence & ApplicationsWhile Vision Transformers (ViTs) have revolutionized computer vision with their exceptional results, they struggle to balance processing speed with visual detail preservation. This tension becomes particularly evident when implementing larger patch sizes.
Heriniaina Andry RABOANARY +2 more
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Data Augmentation for Text Classification Using Autoencoders
IEEE AccessDeep learning models have greatly improved various natural language processing tasks. However, their effectiveness depends on large data sets, which can be difficult to acquire.
Mustafa Cataltas +2 more
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Multi-view-AE: A Python package for multi-view autoencoder models
Journal of Open Source Software, 2023 Ana Lawry Aguila +4 more
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NN-AE-VQE: Neural network parameter prediction on autoencoded variational quantum eigensolvers
A longstanding computational challenge is the accurate simulation of many-body particle systems. Especially for deriving key characteristics of high-impact but complex systems such as battery materials and high entropy alloys (HEA). While simple models allow for simulations of the required scale, these methods often fail to capture the complex dynamics
Mesman, Koen +4 more
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