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Bagchi, Madhubanti (author)
Recently non-image-based data capturing methods such as sensors like RF, ultrasonic or radars, Wi-Fi, Bluetooth, etc for People Counting (PC) applications have gained momentum as an alternative to camera-based systems due to the preference for privacy preservation. Among them mm-wave radars are a strong choice for data capture since they consume...
master thesis 2023
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van Geerenstein, Mathijs (author)
3D object detection models that exploit both LiDAR and camera sensor features are top performers in large-scale autonomous driving benchmarks. A transformer is a popular network architecture used for this task, in which so-called object queries act as candidate objects. Initializing these object queries based on current sensor inputs leads to...
master thesis 2023
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van der Burg, Thijs (author)
Object pushing in robotics has numerous applications, but it often relies on room-bound object tracking systems such as Motion Capture (MoCap) for accurate object pose acquisition. Such systems limit the potential use scenarios, since they add complexity and cost and require expansion of the sensor infrastructure for expanding the operational...
master thesis 2023
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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
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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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Galjaard, Jeroen (author)
Few-shot learning presents the challenging problem of learning a task with only a few provided examples. Gradient-Based Meta-Learners (GBML) offer a solution for learning such few-shot problems. These learners approach the few-shot problem by learning an initial parameterization that requires only a few adaptation steps for new tasks. Although...
master thesis 2023
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Croft, Maxime (author)
This paper presents a novel approach to regional forecasting of SARS-Cov-2 infections one week ahead, which involves developing a municipality level COVID-19 dataset of the Netherlands and using a spatio-temporal graph neural network (GNN) to predict the number of infections. The developed model captures the spread of infectious diseases within...
master thesis 2023
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Lampe, Reinoud (author)
Reducing fuel consumption is an increasingly important topic within aviation. One approach to accomplish this goal is reducing excess fuel weight being loaded on aircraft. Flight dispatchers and pilots load extra fuel to account for uncertainties present in trip fuel consumption, which is currently computed by the flight planning system (FPS)....
master thesis 2022
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CHEN, ENPU (author)
In inspection and display scenarios, reconstructing and rendering the entire surface of a building is a critical step in presenting the overall condition of the building. In building reconstruction, most works are based on point clouds because of their enhanced availability. In recent years, neural radiance fields (NeRF) have become a common...
master thesis 2022
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Lipman, Lars (author)
<b>Introduction </b>- Grasping unknown objects is an important ability for robots in logistic environments. While humans have an excellent understanding of how to grasp objects because of their visual perception and understanding of the 3D world, robotic grasping is still a challenge. Due to the fast-growing development of deep learning methods,...
master thesis 2022
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Lin, Nan (author)
Modular neural networks have received an upsurge of attention lately owing to their unique modular design and potential capacity to decompose complex dynamics and learn interactions among causal variables. Inspired by this potential, we employ the recently introduced Recurrent Independent Mechanisms (RIMs) in the downstream video prediction task...
master thesis 2022
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Singh, Anuj (author)
The versatility to learn from a handful of samples is the hallmark of human intelligence. Few-shot learning is an endeavour to transcend this capability down to machines. Inspired by the promise and power of probabilistic deep learning, we propose a novel variational inference network for few-shot classification (coined as TRIDENT) to decouple...
master thesis 2022
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Claassen, Carlijn (author)
The combination of the high number and the consequences of falls in older adults led to the development of fall risk assessments; non-sensor-based and sensor-based. Multiple studies used ML for older adults' fall risk prediction using raw IMU data. This study's objective was to develop a DL algorithm that predicts the fall risk of people living...
master thesis 2022
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Hazewinkel, Annabel (author)
Pile driving is a widely used technique for the construction of buildings and infrastructure. A popular technique is to vibrate the pile into the sediment. However, since building sites are increasingly being located in metropolitan areas, there is a growing concern about the environmental impact that vibrations may cause during driving....
master thesis 2022
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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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Oerlemans, Marek (author)
In this work, we consider how to optimize an optical system, specifically one with diffractive optical elements (DOE). We start by describing optical theory called Fourier optics also known as wave optics. This type of optics is found by making assumptions from the Maxwell equations for magnetic and electrical fields. This leads us to the...
master thesis 2022
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Sangers, Ruben (author)
Contactless measurement of changes in blood volume by exploiting the color fluctuations in the face is a technique commonly referred to as remote photoplethysmography (rPPG). Recent developments show promising results for heart rate estimation from low-cost cameras, making applications in remote healthcare possible. Remote PPG applications in at...
master thesis 2022
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Haringsma, Jelmer (author)
The main task during operating an automotive vehicle is driving. Nowadays, distractions form a potential risk of claiming the workload necessary for the driving task. Interacting with the User Interface (UI) of the vehicle can be such a distraction. Predicting the next action on the UI can help decrease the risk of distractions. To predict the...
master thesis 2022
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Brouwer, Hans (author)
Synthesizing audio-reactive videos to accompany music is challenging multi-domain task that requires both a visual synthesis skill-set and an understanding of musical information extraction. In recent years a new flexible class of visual synthesis methods has gained popularity: generative adversarial networks. These deep neural networks can be...
master thesis 2022
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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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