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de Beer, Arne (author)This paper presents a study focused on developing an efficient signal processing pipeline and identifying suitable machine learning models for real-time gesture recognition using a testbed consisting of an Arduino Nano 33 BLE and three OPT101 photodiodes. Our research aims to address the challenges of limited computational power whilst...bachelor thesis 2023
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Narchi, William (author)This paper presents how a convolutional neural network can be constructed in order to recognise gestures using photodiodes and ambient light. A number of candidates are presented and evaluated, with the most performant being adopted for in-depth analysis. This network is then compressed in order to be ran on an Arduino Nano 33 BLE...bachelor thesis 2022
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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
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den Heijer, Remco (author)Does a convolutional neural network (CNN) always have to be deep to learn a task? This is an important question as deeper networks are generally harder to train. We trained shallow and deep CNNs and evaluated their performance on simple regression tasks, such as computing the mean pixel value of an image. For these simple tasks we show that...bachelor thesis 2021
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Kotlicki, Bartlomiej (author)Object detection and recognition is a computer vision problem tackled with techniques such as convolutional neural networks or cascade classifiers. This paper tackles the challenge of using the similar methods in the realm of comics strips characters. We approached the idea of combining cascade classifiers with various convolutional neural...bachelor thesis 2021
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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
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van Geerenstein, Mathijs (author), van Mastrigt, Philippe (author), Vergroesen, Laurens (author)This research investigates and describes an image search engine for digital history using deep learning technologies. It is part of the Engineering Historical Memory research, contributing to a multilingual and transcultural approach to decode-encode the treasure of human experience and transmit it to the next generation of world citizens. The...bachelor thesis 2021
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A Literature Study into Hyperparameter Systematization for Deep Learning-based Side-Channel AnalysisMulder, 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
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Groenewegen, Daan (author)In this paper, the DSNet framework used for automatic video summarization gets reviewed when using action localization datasets. The problem facing video summarizations using deep learning techniques is that datasets can be subjective depending on preferences of human annotators, making for noise in the labeling. This paper will look at a anchor...bachelor thesis 2021
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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
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Bechtold, Jeroen (author)This paper tries to combat the food waste of strawberries during the harvesting steps.<br/>An automatic pipeline must be established to combat this food waste.<br/>One of the steps needed in this pipeline is detecting strawberries in images.<br/>Therefore, this paper aims to find out which Convolutional Neural Network (CNN) can be best used to...bachelor thesis 2022
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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
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Karnani, Simran (author)Rhyming words are one of the most important features in poems. They add rhythm to a poem, and poets use this literary device to portray emotion and meaning to their readers. Thus, detecting rhyming words will aid in adding emotions and enhancing readability when generating poems. Previous studies have been done on the topic of poem generation....bachelor thesis 2021
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Papanastasiou, V. S. (author), Trommel, R. P. (author), Harmanny, R. I.A. (author), Yarovoy, Alexander (author)For the first time identification of human individuals using micro-Doppler (m-D) features measured at X-band has been demonstrated. Deep Convolutional Neural Networks (DCNNs) have been used to perform classification. Inspection and visualization of the classification results were performed using Uniform Manifold Approximation and Projection ...conference paper 2021
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Peschl, M. (author)We propose a deep reinforcement learning algorithm that employs an adversarial training strategy for adhering to implicit human norms alongside optimizing for a narrow goal objective. Previous methods which incorporate human values into reinforcement learning algorithms either scale poorly or assume hand-crafted state features. Our algorithm...conference paper 2021
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Yarally, Tim (author), Cruz, Luis (author), Feitosa, Daniel (author), Sallou, J. (author), van Deursen, A. (author)Modern AI practices all strive towards the same goal: better results. In the context of deep learning, the term "results"often refers to the achieved accuracy on a competitive problem set. In this paper, we adopt an idea from the emerging field of Green AI to consider energy consumption as a metric of equal importance to accuracy and to...conference paper 2023
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Bier, H.H. (author), Hidding, A.J. (author), Khademi, S. (author), van Engelenburg, C.C.J. (author), Prendergast, J.M. (author), Peternel, L. (author)Real-world applications of Artificial Intelligence (AI) in architecture have been explored more recently at Technical University (TU) Delft by integrating AI in Design-to-Robotic-Production-Assembly and -Operation (D2RPA&O) methods. These embed robotics into building processes and buildings by linking computational design with robotic...conference paper 2024
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Verduzco, Alejandro (author), Páramo Balsa, Paula (author), Gonzalez-Longatt, Francisco (author), Andrade, Manuel A. (author), Acosta Montalvo, Martha Nohemi (author), Rueda, José L. (author), Palensky, P. (author)This research paper presents a method that uses measurements of voltages angles, as provided by phasor measurement units (PMU), to accurately detect the sudden disconnection of a generation unit from a power grid. Results in this research paper have demonstrated, in a practical fashion, that a multi-layer perceptron (MLP) neural network (NN) can...conference paper 2022
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Corradi, Federico (author), Fioranelli, F. (author)The advent of consumer and industrial Unmanned Aerial Vehicles (UAVs), commonly referred to as drones, has opened business opportunities in many fields, including logistics, smart agriculture, inspection, surveillance, and construction. In addition, the autonomous operations of UAVs reduce risks by minimizing the time spent by human workers...conference paper 2022
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Myers, N.J. (author), Kwon, Hyukjoon (author), Ding, Yacong (author), Song, Kee-Bong (author)In this paper, we propose a learning-aided signal processing solution for channel estimation in 5G new radio (NR). Channel estimation is an important algorithm for baseband modem design. In 5G NR, estimating the channel is challenging due to two reasons. First, the pilot signals are transmitted over a small fraction of the available time...conference paper 2021