Searched for: subject%3A%22Supervising%22
(21 - 40 of 155)

Pages

document
Farah, Youssef (author)
Event cameras are novel bio-inspired sensors that capture motion dynamics with much higher temporal resolution than traditional cameras, since pixels react asynchronously to brightness changes. They are therefore better suited for tasks involving motion such as motion segmentation. However, training event-based networks still represents a...
master thesis 2023
document
CHANOPOULOU, IOANNA (author)
Convolutional Neural Networks (CNNs) have emerged primarily from research focusing on image classification tasks and as a result, most of the well-motivated design choices found in literature are relevant to computer vision applications. CNNs' application on Imaging Mass Spectrometry (IMS) data is quite recent and involves new challenges, such...
master thesis 2023
document
Lammers, Laurens (author)
Neuromorphic sensors, like for example event cameras, detect incremental changes in the sensed quantity and communicate these via a stream of events. Desired properties of these signals such as high temporal resolution and asynchrony are not always fully exploited by algorithms that process these signals. Spiking neural networks (SNNs) have...
master thesis 2023
document
Achy, Nils (author)
This research paper proposes a deep learning model to infer segments of speaking intentions using body language captured by a body-worn accelerometer. The objective of the study is to detect instances where individuals exhibit a desire to speak based on their body language cues. The labeling scheme employed is a binary string, with “0”...
bachelor thesis 2023
document
Dijkstra, Jonathan (author)
In recent years, the agricultural sector has seen significant techno- logical improvements under the flag of precision agriculture, assisting farmers in the manageability that coincides with large-scale farming. Moreover, precision agriculture aims to enable plant-specific farming on the macro scale that is demanded by the current global...
master thesis 2023
document
den Ridder, Luc (author)
Although deep reinforcement learning (DRL) is a highly promising approach to learning robotic vision-based control, it is plagued by long training times. This report introduces a DRL setup that relies on self-supervised learning for extracting depth information valuable for navigation. Specifically, a literature study is conducted to investigate...
master thesis 2023
document
Spengler, Daniel (author)
The study of tumor microenvironments (TMEs) and immune cell composition in cancer, a disease characterized by uncontrolled growth and spread of tumor cells, has become increasingly important for understanding tumor progression and patient outcomes. Tools such as the TME-Analyzer enable this kind of research, but their manual workflows highlight...
master thesis 2023
document
Beets, Simon (author)
master thesis 2023
document
Cui, Jianfeng (author)
We explored the possibility of improving cross-view matching performance with self-supervised learning techniques and perform interpretations in terms of the embedding space of image features. The effect of pre-training by contrastive learning is verified quantitatively by experiments, and also exhibited by visualization of the feature space.
master thesis 2023
document
Moradi, M. (author), Chiachío, Juan (author), Zarouchas, D. (author)
Composite structures are highly valued for their strength-to-weight ratio, durability, and versatility, making them ideal for a variety of applications, including aerospace, automotive, and infrastructure. However, potential damage scenarios like impact, fatigue, and corrosion can lead to premature failure and pose a threat to safety. This...
conference paper 2023
document
Moradi, M. (author), Gul, F.C. (author), Chiachío, Juan (author), Benedictus, R. (author), Zarouchas, D. (author)
A health indicator (HI) serves as an intermediary link between structural health monitoring (SHM) data and prognostic models, and an efficient HI should meet prognostic criteria, i.e., monotonicity, trendability, and prognosability. However, designing a proper HI for composite structures is a challenging task due to the complex damage...
conference paper 2023
document
Picek, S. (author), Perin, G. (author), Mariot, L. (author), Wu, L. (author), Batina, Lejla (author)
Side-channel attacks represent a realistic and serious threat to the security of embedded devices for already almost three decades. A variety of attacks and targets they can be applied to have been introduced, and while the area of side-channel attacks and their mitigation is very well-researched, it is yet to be consolidated. Deep learning...
journal article 2023
document
Zhang, Lanxin (author), Dong, Y. (author), Farah, H. (author), Zgonnikov, A. (author), van Arem, B. (author)
Detecting abnormal driving behavior is critical for road traffic safety and the evaluation of drivers' behavior. With the advancement of machine learning (ML) algorithms and the accumulation of naturalistic driving data, many ML models have been adopted for abnormal driving behavior detection. Most existing ML-based detectors rely on (fully)...
poster 2023
document
Anderson, David M G (author), Kotnala, Ankita (author), Migas, L.G. (author), Patterson, N. Heath (author), Tideman, L.E.M. (author), Ach, Thomas (author), Tortorella, Sara (author), Van de Plas, Raf (author), Curcio, Christine A. (author), Schey, Kevin L. (author)
Introduction: Age related macular degeneration (AMD) causes legal blindness worldwide, with few therapeutic targets in early disease and no treatments for 80% of cases. Extracellular deposits, including drusen and subretinal drusenoid deposits (SDD; also called reticular pseudodrusen), disrupt cone and rod photoreceptor functions and strongly...
journal article 2023
document
Dong, Y. (author), Chen, Kejia (author), Ma, Zhiyuan (author)
Condition-based maintenance is becoming increasingly important in hydraulic systems. However, anomaly detection for these systems remains challenging, especially since that anomalous data is scarce and labeling such data is tedious and even dangerous. Therefore, it is advisable to make use of unsupervised or semi-supervised methods, especially...
conference paper 2023
document
Liu, C. (author), Xu, Y. (author), van Kampen, E. (author), de Croon, G.C.H.E. (author)
In this paper, we propose an obstacle avoidance solution for a 34-gram quadcopter equipped with a monocular camera. The perception of obstacles is tackled by a lightweight convolutional neural network predicting a dense depth map from a captured grey-scale image. The depth network performs self-supervised learning and thus requires no ground...
journal article 2023
document
Ghorbani, R. (author), Reinders, M.J.T. (author), Tax, D.M.J. (author)
With the progress of sensor technology in wearables, the collection and analysis of PPG signals are gaining more interest. Using Machine Learning, the cardiac rhythm corresponding to PPG signals can be used to predict different tasks such as activity recognition, sleep stage detection, or more general health status. However, supervised...
conference paper 2023
document
Eftekhar, Z. (author), Pel, A.J. (author), van Lint, J.W.C. (author)
Global System for Mobile Communications (GSM) data provides valuable insights into travel demand patterns by capturing people's consecutive locations. A major challenge, however, is how the polling interval (PI; the time between consecutive location updates) affects the accuracy in reconstructing the spatio-temporal travel patterns. Longer...
journal article 2023
document
Moradi, M. (author), Broer, Agnes A.R. (author), Chiachío, Juan (author), Benedictus, R. (author), Loutas, Theodoros H. (author), Zarouchas, D. (author)
A health indicator (HI) is a valuable index demonstrating the health level of an engineering system or structure, which is a direct intermediate connection between raw signals collected by structural health monitoring (SHM) methods and prognostic models for remaining useful life estimation. An appropriate HI should conform to prognostic...
journal article 2023
document
Viering, T.J. (author), Loog, M. (author)
Learning curves provide insight into the dependence of a learner's generalization performance on the training set size. This important tool can be used for model selection, to predict the effect of more training data, and to reduce the computational complexity of model training and hyperparameter tuning. This review recounts the origins of...
review 2023
Searched for: subject%3A%22Supervising%22
(21 - 40 of 155)

Pages