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Deep Learning Fusion of Monocular and Stereo Depth Maps Using Convolutional Neural Networks

Tóth, Dani (author)

This paper presents an encoder-decoder-style convolutional neural network (CNN) for the purpose of improving monocular and stereo depth estimation (SDE) estimates, by combining them with the corresponding monocular estimates through a fusion network, assisted by prior information to provide context for the fusion. Video cameras are commonly used...

master thesis 2024

document

Finding the Needle in the Pre-Trained Model Zoo: The Use of Rich Metadata and Graph Learning to Estimate Task Transferability

van der Wilk, Hilco (author)

The democratization of machine learning through public repositories, often known as model zoos, has significantly increased the availability of pre-trained models for practitioners. However, this abundance can make it difficult to choose the most suitable pre-trained model for fine-tuning on new tasks. Although various methods have been proposed...

master thesis 2024

document

Automatic Prostate Volume estimation on Transabdominal Ultrasound using Deep Neural Networks

Kurucz, Liza (author)

Prostate cancer is the most commonly diagnosed cancer in the Netherlands. Accurate assessment of the prostate volume (PV) is a crucial step in prostate cancer (PCa) screening and risk-stratification. In standard clinical care, the PV is obtained by measuring the prostate dimensions with the aid of transrectal ultrasound (TRUS). However, rectal...

master thesis 2024

document

Inclined quadrotor landing using on-board sensors and computing

Cancrinus, Ernst (author)

<div>Achieving autonomous inclined landing would be an important step towards quadrotors which are able to land anywhere and under any conditions. If a quadrotor is able to safely land anywhere, even when a landing platform is not available, this would open up many useful applications. Firstly, the quadrotor could safely land whenever its...

master thesis 2024

document

Affective Active Inference and Precision Estimation: A representation of affective feelings in active inference contsex

Timmer, Sebastiaan (author)

<div>As Neuroscience progresses, there is an increasing amount of research that endorses predictions and reducing of prediction errors as one of the main functions of the brain. active inference is a brain-inspired, mathematical framework that successfully implements this idea both in simulations as well as in robotics. The predictive nature of...

master thesis 2024

document

Cost Estimation for Factorized Machine Learning

te Marvelde, Pepijn (author)

In the realm of machine learning (ML), the need for efficiency in training processes is paramount. The conventional first step in an ML workflow involves collecting data from various sources and merging them into a single table, a process known as materialization, which can introduce inefficiencies caused by redundant data. Factorized ML strives...

master thesis 2024

document

Towards Adaptive Biodynamic Feedthrough Modeling for Touchscreen Applications

Iancu, Alexandru (author)

Given the expected increase of automation in the vehicles of the future, touchscreens are expected to be used in a wide variety of scenarios, including the ones that can become safety-critical.<br/>One disadvantage of the direct interaction approach that characterizes touchscreen operation is the feedthrough of accelerations through the human...

master thesis 2024

document

Pose Estimation of an Unknown Uncooperative Target Using LiDAR & Thermal Infrared Fusion

Creagh, Conor (author)

In recent years, researchers have proposed a variety of approaches to tackle the problem of orbital debris. Debris targets are diverse, and prior knowledge may be limited, with unknown uncooperative debris targets being the most challenging category. A crucial portion of any debris capture scenario is the observation phase during the approach....

master thesis 2024

document

Power to the airborne wind energy performance model: Estimating long-term energy production with an emphasis on pumping flexible-kite systems

Schelbergen, M. (author)

The potential of utility-scale airborne wind energy (AWE) systems to contribute significantly to the energy transition hinges on their large-scale deployment, which depends on the cost-competitiveness and complementarity with conventional wind turbines. Central to the assessment of these metrics is understanding long-term energy production,...

doctoral thesis 2024

document

Tackling the weathering with low ranks: Handling the complex near surface of land seismic data with low-rank-based methods

Alfaraj, Ali (author)

Imaging and inversion with seismic data recorded with sources and receivers at the surface are powerful tools to infer knowledge about the subsurface. However, creating an image with seismic data is unfortunately not as easy as taking a picture with a smartphone. The estimated subsurface models in many situations are far from ideal due to the...

doctoral thesis 2024

document

Sensor Fusion for Visual-Inertial Simultaneous Localisation and Mapping: Applied and tested on a small ground-based mini rover

Bekkers, Sam (author)

The generation of a 3D map of an unseen environment, obtained through solving the SLAM problem, is a popular topic currently in the robotics domain. The Lunar Rover Mini (LRM) at the German Aerospace Center solves this problem using a RGB-D camera system, which is favourable in space applications due to its lightweight characteristics and energy...

master thesis 2024

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Flying and Ground Robot Collaboration for Camera-based Search and Rescue

Esteves Henriques, Bernardo (author)

Search and Rescue (SaR) missions present challenges due to the complexity of the disaster scenarios. Most life losses and injuries occur in developing countries. Robotics has become indispensable for rapidly locating disaster victims. Combining flying and ground robots more effectively serves this purpose due to their complementary features. To...

master thesis 2024

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Evaluating 6D pose estimation accuracy with synthetic data: A comparative analysis of RGB based and RGB-Depth-based images in a chess piece picking task with a robotic arm

Waterhout, Max (author)

This study investigates the influence of synthetic data on the accuracy of 6D pose estimation in RGB images compared to RGB-Depth image-based methods. Additionally, it aims to examine how this performance varies across different types of small chess pieces during a picking task with a robotic arm. The methodology involves 3D scanning the chess...

master thesis 2024

document

Review of Integrated Chassis Control Techniques for Automated Ground Vehicles

Skrickij, Viktor (author), Kojis, Paulius (author), Šabanovič, Eldar (author), Shyrokau, B. (author), Ivanov, Valentin (author)

Integrated chassis control systems represent a significant advancement in the dynamics of ground vehicles, aimed at enhancing overall performance, comfort, handling, and stability. As vehicles transition from internal combustion to electric platforms, integrated chassis control systems have evolved to meet the demands of electrification and...

review 2024

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Linear Time-Varying Parameter Estimation: Maximum A Posteriori Approach via Semidefinite Programming

Vakili, S. (author), Khosravi, M. (author), Mohajerin Esfahani, P. (author), Mazo, M. (author)

We study the problem of identifying a linear time-varying output map from measurements and linear time-varying system states, which are perturbed with Gaussian observation noise and process uncertainty, respectively. Employing a stochastic model as prior knowledge for the parameters of the unknown output map, we reconstruct their estimates...

journal article 2024

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Transfer learning-based methodologies for Dynamic Thermal Rating of transmission lines

Paldino, Gian Marco (author), De Caro, Fabrizio (author), De Stefani, J. (author), Vaccaro, Alfredo (author), Bontempi, Gianluca (author)

Dynamic Thermal Rating (DTR) enhances grid flexibility by adapting line capabilities to weather conditions. For this purpose, DTR-based technologies require reliable and continuous measurement of the conductor temperature along the line route, which could hinder their wide-scale deployment due to the prohibitively high number of required...

journal article 2024

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Predictive machine learning in earth pressure balanced tunnelling for main drive torque estimation of tunnel boring machines

Glab, K. (author), Wehrmeyer, G. (author), Thewes, M. (author), Broere, W. (author)

Designing the main drive motor capacity of Earth Pressure Balanced Tunnel Boring Machines (EPB TBMs) is a crucial task for every EPB tunnelling project. The machine needs to be equipped with sufficient power to master the geotechnical conditions of the respective project. On the other hand, overpowering the machine should be avoided for...

journal article 2024

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The One Step Malliavin scheme: new discretization of BSDEs implemented with deep learning regressions

Négyesi, B. (author), Andersson, Kristoffer (author), Oosterlee, Cornelis W. (author)

A novel discretization is presented for decoupled forward–backward stochastic differential equations (FBSDE) with differentiable coefficients, simultaneously solving the BSDE and its Malliavin sensitivity problem. The control process is estimated by the corresponding linear BSDE driving the trajectories of the Malliavin derivatives of the...

journal article 2024

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High-Confidence Data-Driven Ambiguity Sets for Time-Varying Linear Systems

Boskos, D. (author), Cortes, Jorge (author), Martinez, Sonia (author)

This paper builds Wasserstein ambiguity sets for the unknown probability distribution of dynamic random variables leveraging noisy partial-state observations. The constructed ambiguity sets contain the true distribution of the data with quantifiable probability and can be exploited to formulate robust stochastic optimization problems with out...

journal article 2024

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Convolutional Cross-View Pose Estimation

Xia, Z. (author), Booij, O. (author), Kooij, J.F.P. (author)

We propose a novel end-to-end method for cross-view pose estimation. Given a ground-level query image and an aerial image that covers the query&amp;#x0027;s local neighborhood, the 3 Degrees-of-Freedom camera pose of the query is estimated by matching its image descriptor to descriptors of local regions within the aerial image. The...

journal article 2024