Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 5 of 5 for “"Residual Neural Network"”.
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Vehicle Detection in Deep Learning
… detection model, adopting one of the classical neural networks, which are the residual neural network and the region proposal network. The model utilizes the residual neural network as a feature extractor and the region proposal network to detect the potential objects' information.
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Multi-dimensional computational imaging from diffraction intensity using deep neural networks
… with a regularized inversion using deep neural networks for two- and three-dimensional applications. The inversion process begins with the definition of a forward physical model that relates a diffraction intensity to a phase object and then involves a physics-informing step (or …
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Partial Discharges: Experimental Investigation, Model Development, and Data Analytics
… For the second target, it is aimed to use deep neural networks to identify and discriminate different sources of PD. The measurement data are used to generate thousands of phase-resolved PD (PRPD) images that will be used for training deep learning models. To meet the characteristics of the …
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Physics-based and data-driven inversion of magnetotelluric data for subsurface imaging
… ensemble-based conditioning with physics-guided residual learning. The approach combines an ensemble-approximated conditional Gaussian process (EnsCGP), which produces physically consistent resistivity estimates and ensemble-based uncertainty within the span of a prior model space, with a …
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Agricultural crop residue cover estimation using image analysis and machine learning
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2025-08-01