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 7 of 7 for “"Hybrid Transformer"”.
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Automated and Handcrafted Neural Network Design for Vision Applications
… for pedestrian trajectory prediction and a hybrid transformer-convolutional network for video deraining. To facilitate the applications of designed neural networks, the thesis further presents a semi-supervised learning based framework that leverages only a few labelled data instead of …
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Learning representations for information mining from text corpora with applications to cyber threat intelligence
… cyber threat entities, types, and events. Using hybrid transformer-based implementations of these learning models, CTI-relevant key phrases are identified, and specific cyber threats are classified using classification models based upon graph neural networks (GNNs). The central scientific goal …
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Power Converter and Control Design for High-Efficiency Electrolyte-Free Microinverters
… boost ratio dc-dc converter topologies using the hybrid transformer concept are presented in this dissertation. The proposed converters have improved magnetic and device utilization. Combine these features with the converter's reduced switching losses which results in a low cost, simple structure …
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OrganixInsights: High throughput imaging and high content screening of organoids
… microscopy data. First, we introduce Deconv3D, a hybrid transformer–convolution architecture designed for volumetric microscopy restoration. The model integrates convolutional feature extraction with windowed self-attention modules to capture both local spatial features and long-range contextual …
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Application of data-driven neural networks to bio-inspired lattice design and prediction of multiphysics solution fields
… parameter-based geometry generation framework. A hybrid Transformer-GRU model is trained on geometric features and serves as an efficient surrogate for FEA, enabling rapid exploration of the design space and facilitating impact-resistant design optimization. Inverse design through a genetic …
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Integration of broadband direct-conversion quadrature modulators
… the CMOS one utilizes a coil-transmission line hybrid transformer at its LO input to drive the switchable PP filters.
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Deep learning for size-agnostic two-phase flow simulation with realistic pore structures and rock-fluid properties
… demands. I subsequently introduce a hybrid transformer-convolutional neural network that performs drainage based solely on pore size, with phase connectivity enforced as a post-processing step. This approach facilitates inference for images of various sizes and accommodates any fluid …