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 20 of 77 for “"Learning-based Methods"”.
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Monocular Visual Inertial Odometry using Learning-based Methods
… reality.</p> <p>This study develops three novel learning-based approaches to Odometry estimation using a monocular camera and inertial measurement unit. The networks are well-trained on standard datasets, KITTI and EuROC, and a custom dataset using supervised, unsupervised and semi-supervised …
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Deep learning-based methods for parametric shape prediction
… time-consuming process. While advances in deep learning have been successfully applied to noisy geometric data, the task of generating parametric shapes has so far been difficult for these methods. In this thesis, we consider the task of deep parametric shape prediction from two distinct angles. …
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Integration of Model- and Learning-based Methods in Image Restoration
Following the spectacular success of deep learning algorithms in image restoration tasks, there is growing interest in exploring how to combine the practical advantages of learning-based methods with the theoretical understanding that comes from model-based approaches. In fact, while deep learning …
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Structuring Optimal Control of Legged Locomotion with Learning-based Methods
Both optimal control methods and learning-based methods have been widely used for the control of legged locomotion. While optimal control formulations allow the designer to guarantee constraints on the solutions found, learning-based methods can leverage data and past experiences to globally search …
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Learning-Based Methods for Spacecraft Dynamics Modeling, Filtering, and Predictive Control
… grappled objects. Traditionally, adaptive model-based control approaches have relied on an analytical dynamics model with a set of parameters that are estimated from observations of effective spacecraft dynamics. Without extensive a priori knowledge of the system under study, however, it can be …
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Comparison of Machine Learning-Based Methods for Narrowband Blind Adaptive Beamforming
… and interferer cancellation. The earliest methods of beamforming assumed prior knowledge of the receive array geometry and of the incoming signal directions. This information is normally found via array calibration. Blind source separation methods do not require this information and …
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Learning-based Methods for Occluder-aided Non-Line-of-Sight Imaging
… a diffuse surface. In particular, we develop a learning-based method that discovers hidden cues in the shadows and relies on building synthetic scenes composed of 3D face models obtained from a single photograph of each identity. We transfer what we learn from the synthetic data to the real data …
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Exploring deep learning based methods for information retrieval in Indian classical music
… collections. In this work, we propose a deep learning based approach to Raga recognition. Our approach employs efficient pre-possessing and learns temporal sequences in music data using Long Short Term Memory based Recurrent Neural Networks (LSTM-RNN). We train and test the network on smaller …
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Machine Learning based Methods to Improve Power System Operation under High Renewable Pennetration
… these problems are complex, advances in machine learning and artificial intelligence provide opportunities for novel paradigms for addressing the challenges. The overall aim of the dissertation is to harness data-driven and model-based techniques and develop computationally efficient tools for …
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Learning-Based Methods for Enabling On-Edge, Accurate, Sustainable, and Human-Centered Intelligent Manufacturing
L'abstract è presente nell'allegato / the abstract is in the attachment
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Deep Learning Based Methods for Automatic Extraction of Syntactic Patterns and their Application for Knowledge Discovery
… To address this gap, I introduce an attention-based supervised deep learning model, ASPER. ASPER is designed to extract SDPs that denote semantic relationships between entities within a given sentential context. I rigorously evaluate the performance of ASPER across three distinct semantic …
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An Experimental Evaluation of Learning-Based Methods for Loop Closure Detection in Simultaneous Localization and Mapping
… detect loop closures, against recently developed learning-based approaches. In particular, our first contribution is to benchmark established techniques based on hand-crafted descriptor matching against novel learning-based approaches based on neural networks (i.e., SuperPoint and SuperGlue). As a …
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Learning-based Methods for Fault Detection in Fiber-Optic Networks: Monitoring under Domain Shifts and Limited Supervision
L'abstract è presente nell'allegato / the abstract is in the attachment
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Introducing statistical and machine learning-based methods of enhancing the resiliency and security of electrical-based critical infrastructure
… has been performed to improve electrical-based technology’s capability, scale, resiliency, and security. This study focuses solely on resiliency and security, both of which require efficient data collection, storage, and processing. In the case of the resiliency of high-voltage electrical …
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Natural language processing and learning-based methods for enhancing automation, alignment, and interpretability in model-driven planning, monitoring, and control of construction projects
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-08-01
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Enhancing cross-dataset performance in distracted driver detection using body part activity recognition.
… task, and the literature proposes various deep learning-based methods. Among these methods, convolutional neural networks dominate because they can extract and learn image features automatically. However, even though existing methods have reported remarkable results, the cross-dataset …
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Deep learning in sequential data analysis
Deep learning has achieved great success in recent years in computer vision and its related areas. For core computer vision tasks such as image classification, image semantic segmentation, image super-resolution, and object detection from images, deep learning based methods outperform various …
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Deep Learning-based Numerical Methods for Stochastic Partial Differential Equations and Applications
… and Warin [15], we propose and study the deep learning-based methods for both the forward and backward SPDEs. In particular, the forward SPDEs may allow for Neumann boundary conditions. We also prove the convergence analysis of the proposed algorithms. The numerical results indicate that the …
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SIMULTANEOUS ARTIFACTS CORRECTION AND ACCELERATION FOR CHEMICAL EXCHANGE SATURATION TRANSFER IMAGING VIA DEEP LEARNING
… exogenous administered contrast agents. CEST MRI methods rely on molecular signal saturation through radiofrequency pulses with the same frequency as a prescribed molecule (e.g., glutamate) to be measured in a magnetic field. Because the background signal from water modular is generally greater …
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