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Datta, Leonid (author)
Training Convolutional Neural Network (CNN) models is difficult when there is a lack of labeled training data and no unlabeled data is available. A popular method for this is domain adaptation where the weights of a pre-trained CNN model are transferred to the problem setup. The model is pre-trained on the same task but in a different domain...
master thesis 2020
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Wasei, E.A.A. (author)
Physics-Informed Neural Networks (PINNs) are a new class of numerical methods for solving partial differential equations (PDEs) that have been very promising. In this paper, four different implementations will be tested and compared. These include: the original PINN functional with equal weights for the interior and boundary loss, the same...
bachelor thesis 2020
document
Cian, David (author)
In this paper, we run two methods of explanation, namely LIME and Grad-CAM, on a convolutional neural network trained to label images with the LEGO bricks that are visible in them. We evaluate them on two criteria, the improvement of the network's core performance and the trust they are able to generate for users of the system. We nd that in...
bachelor thesis 2020
document
Yin, Rukai (author)
System Dynamics (SD) is an approach to study the nonlinear behaviour of complex systems over time. SD models provide a high­level understanding of the system and aid in designing policies to achieve specific system behaviours. Conventional SD modelling requires an intensive amount of time, human resources and effort. Applying Machine Learning ...
master thesis 2020
document
Bougrimov, Denis (author)
The advantage of using protons to irradiate a tumour in cancer treatment, is that the energy can be delivered very precisely to the tumour without irradiating much of the surrounding tissue. The disadvantage of this is that small displacements of a patient can result in large deviations in the planned dose delivery according to the treatment...
bachelor thesis 2020
document
Kaniouras, Pantelis (author)
Road network maps facilitate a great number of applications in our everyday life. However, their automatic creation is a difficult task, and so far, published methodologies cannot provide reliable solutions. The common and most recent approach is to design a road detection algorithm from remote sensing imagery based on a Convolutional Neural...
master thesis 2020
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van Lil, Wouter (author)
Using transfer learning, convolutional neural networks for different purposes can have similar layers which can be reused by caching them, reducing their load time. Four ways of loading and executing these layers, bulk, linear, DeepEye and partial loading, were analysed under different memory constraints and different amounts of similar networks...
bachelor thesis 2020
document
Mulder, Doreen (author)
With the recent increase in computational power, deep learning is being applied in many different fields. Deep learning has produced promising results in the field of side-channel analysis. However, the algorithms used to construct deep neural networks remain black boxes, which makes it hard to fully employ the capabilities of attacks performed...
bachelor thesis 2020
document
Davidse, Davy (author)
This thesis discusses the application of deep learning to Coherent Fourier<br/>Scatterometry data in order to quickly and reliably detect nanoparticles on<br/>surfaces. An introduction to deep learning is followed by a review of the<br/>experimental setup and used software. After that, results are presented of<br/>classification accuracy tests...
master thesis 2020
document
Dijkstra, Fokke (author)
A variety of statistical methods are available to detect sudden changes, or breakpoints, in time series when used as multi-temporal change detection technique. However, these methods are unreliable in the presence of noise. Neural nets might detect breakpoints better. These deep learning models are able to generalize and optimize well, even in...
master thesis 2020
document
Basu, S. (author), Watson, S.J. (author), Lacoa Arends, Eric (author), Cheneka, B.R. (author)
A hybrid neural network model, comprising of a convolutional neural network and a multilayer perceptron network, has been developed for day-ahead forecasting of regional scale wind power production. This model requires operational weather forecasts as input and also has the capability to ingest data from ensemble forecasts. Even though the...
conference paper 2020
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Jia, Mu (author), Li, Shaoxuan (author), Le Kernec, Julien (author), Yang, Shufan (author), Fioranelli, F. (author), Romain, Olivier (author)
As the number of older adults increases worldwide, new paradigms for indoor activity monitoring are required to keep people living at home independently longer. Radar-based human activity recognition has been identified as a sensing modality of choice because it is privacy-preserving and does not require end-users compliance or manipulation. In...
conference paper 2020
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Jiang, Shijie (author), Zheng, Yi (author), Solomatine, D.P. (author)
Modeling dynamic geophysical phenomena is at the core of Earth and environmental studies. The geoscientific community relying mainly on physical representations may want to consider much deeper adoption of artificial intelligence (AI) instruments in the context of AI's global success and emergence of big Earth data. A new perspective of using...
journal article 2020
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Roy, Devjeet (author), Zhang, Ziyi (author), Ma, Maggie (author), Arnaoudova, Venera (author), Panichella, A. (author), Panichella, Sebastiano (author), Gonzalez, Danielle (author), Mirakhorli, Mehdi (author)
Automated test case generation tools have been successfully proposed to reduce the amount of human and infrastructure resources required to write and run test cases. However, recent studies demonstrate that the readability of generated tests is very limited due to (i) uninformative identifiers and (ii) lack of proper documentation. Prior...
conference paper 2020
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Wang, H. (author), Nunez, Alfredo (author)
The catenary insulator maintains electrical insulation between catenary and ground. Its defects may happen due to the long-term impact from vehicle and environment. At present, the research of defect detection for catenary insulator faces several challenges. 1) Localization accuracy is low, which causes the localized object to be incomplete or...
journal article 2020
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Adank, Marloes (author)
Objective: Recent studies have suggested an association between age-related hearing loss and cognitive decline. Yet, the underlying mechanism explaining this relation remains unknown. In this regard, several studies investigated gray matter (GM) differences in age-related hearing loss but presented inconsistent results regarding the association...
master thesis 2019
document
Jurasiński, Karol (author)
Recently, deep generative models have been shown to achieve state-of-the-art performance on semi-supervised learning tasks. In particular, variational autoencoders have been adopted to use labeled data, which allowed the development of SSL models with the usage of deep neural networks. However, some of these models rely on ad-hoc loss additions...
master thesis 2019
document
Freiherr von der Goltz, Julian (author)
Aircraft inspections after unexpected incidents, like lightning strikes, currently require a timeconsuming and costly inspection process, due to the small size of the lightning strike damages. Mainblades Inspections is working on an automated, drone-based solution, that scans the aircraft hull with a high-resolution camera. The objective of this...
master thesis 2019
document
Maan, Riya (author)
Speech recognition systems can be found all around us. From personal assistants in mobile phones and smart speakers to robots, we use speech recognition systems everyday. However, communicating with them can be troublesome in noisy environments because they only use audio signals for speech recognition. This problem can be solved by using visual...
master thesis 2019
document
Zhou, Zequn (author)
Urban areas are rapidly expanding in developing countries. One of goals of the United Nations Human Settlement Programme (UN-Habitat) is to understand and guide urban development for some developing regions.<br/>Currently, the approaches that UN-Habitat is using cost plenty of workforce, material, and time. Therefore, UN-Habitat is interested in...
master thesis 2019
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