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Triana de las Heras, Javier (author)
Technological advances, cost reduction, depletion of fossil fuels, environmental concerns, and growing energy demand are expanding photovoltaic solar energy (PV) in more latitudes and locations. A simple and effective procedure to assess the PV potential of a particular region is to analyse its climatic conditions. In general, climatic studies...
master thesis 2023
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Ries, Maxmillan (author)
Training deep learning models for time-series prediction of a target population often requires a substantial amount of training data, which may not be readily available. This work addresses the challenge of leveraging multiple related sources of time series data in the same feature space to improve the prediction performance of a deep learning...
master thesis 2023
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Lückerath, Femke (author)
During the initial phase of diagnosis, patients with anti-NDMA-receptor encephalitis (anti-NMDARE) often experience severe symptoms that significantly impact their quality of life. Anti-NDMARE is an autoimmune disorder affecting the brain, with electroencephalography (EEG) playing a vital role in diagnosis and treatment. Identifying EEG patterns...
master thesis 2023
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Wubben, Luuk (author)
Outlier detection is an essential part of modern systems. It is used to detect anomalies in behaviour or performance of systems or subjects, such as fall detection in smartwatches or voltage irregularity detection in batteries. This provides early indications of something of potential problems.<br/><br/>A part of outlier detection that is not...
bachelor thesis 2023
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Wang, Yunhan (author)
Temporal Action Localization (TAL) aims to localize the start and end times of actions in untrimmed videos and classify the corresponding action types. TAL plays an important role in understanding video. Existing TAL approaches heavily rely on deep learning and require large-scale data and expensive training processes. Recent advances in...
bachelor thesis 2023
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Dai, Anthony (author), van de Weg, Joris (author)
In the context of designing a real-time brain-computer interface for playing a game using the OpenBCI Ultracortex "Mark IV" headset, this paper focuses on the work of the decoding subgroup. The primary responsibility is to analyse EEG data retrieved from the OpenBCI headset and classify the intention of the user. Our objective is to achieve a...
bachelor thesis 2023
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Backer, Suzanne (author)
In the machine learning research community, significant importance is given to the optimization of techniques which are employed once a benchmark dataset is given. However, less importance is assigned to the quality of these datasets and to how these datasets are obtained. In this work, we look into annotation practices in the research area of...
bachelor thesis 2023
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Oudhuis, Waded (author)
Computers having the ability to estimate intentions to speak can improve human-computer interaction. While plenty of research has been done on next-speaker prediction, they differ from intentions to speak since these rely only on the person themselves. Previous research was done on inferring intentions to speak using accelerometer data with some...
bachelor thesis 2023
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Tjong, Jonathan (author)
For causal inference, sufficient overlap is needed. It is possible to use propensity scores with the positivity assumption to ensure overlap is present. However, positivity is not enough to properly identify the region of overlap. For this, propensity scores need to be used in combination with density estimation. This project aims to evaluate...
bachelor thesis 2023
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Witting, Emiel (author)
Domain adaptation allows machine learning models to perform well in a domain that is different from the available train data. This non-trivial task is approached in many ways and often relies on assumptions about the source (train) and target (test) domains. Unsupervised domain adaptation uses unlabeled target data to mitigate a shift or bias...
bachelor thesis 2023
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Socol, Codrin (author)
Learning curves are used to shape the performance of a Machine Learning (ML) model with respect to the size of the set used for training it. It was commonly thought that adding more training samples would increase the model's accuracy (i.e., they are monotone), but recent works show that may not always be the case. In other words, some learners...
bachelor thesis 2023
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van Marken, Julie (author)
This research aims to answer the question whether non-verbal vocal behavior can be used to estimate intention to speak. To answer this question data from a dutch social networking event is used to gather intentions to speak. The intentions to speak are split up in two categories: successful and unsuccessful intentions. The unsuccessful...
bachelor thesis 2023
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Ibrahim, Ahmed (author)
This systematic review investigates the practices and implications of human annotations in machine learning (ML) research. Analyzing a selection of 100 papers from the IEEE Access Journal, the study explores the data collection and reporting methods employed. The findings reveal a prevalent lack of standardization and formalization in the...
bachelor thesis 2023
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Sīpols, Emīls (author)
Federated learning (FL) has emerged as a promis-ing approach for training machine learning models using geographically distributed data. This paper presents a comprehensive comparative study of var-ious machine learning models in the context of FL. The aim is to evaluate the efficacy of these models in different data distribution scenarios and...
bachelor thesis 2023
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Sav, Andra (author)
Machine Learning models are nowadays infused into all aspects of our lives. Perhaps one of its most common applications regards recommender systems, as they facilitate users' decision-making processes in various scenarios (e.g., e-commerce, social media, news, online learning, etc.). Training performed on large volumes of data is what ultimately...
bachelor thesis 2023
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Bastow, Timothy (author)
There is mounting evidence indicating a relation- ship between the gut microbiome composition and the development of mental diseases but the mech- anisms remain unclear. Shotgun sequenced data from 90 schizophrenic patients and 81 sex, age, weight, and location matched controls was used for three machine learning models: Logistic Re- gression,...
bachelor thesis 2023
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Sassoon, Jordan (author)
Contrastive Language-Image Pretraining (CLIP) has gained vast interest due to its impressive performance on a variety of computer vision tasks: image classification, image retrieval, action recognition, feature extraction, and more. The model learns to associate images with their descriptions, a powerful method which allows it to perform well on...
bachelor thesis 2023
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Vilhjálmsson, Thor (author)
This thesis aims to investigate the feasibility of developing a successful unsupervised Structural Health Monitoring (SHM) methodology to detect damage in structures, specifically bridges. Detecting damage, especially in its earliest stages, is challenging, thus prompting the need for robust and effective methods. The success of such a...
master thesis 2023
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Sheremet, Denys (author)
In AutoML, the search space of possible pipelines is often large and multidimensional. This makes it very important to use an efficient search algorithm. We measure the effectiveness of the Metropolis-Hastings algorithm (M-H) in a pipeline synthesis framework, when the search space is described by a context-free grammar. We also compare the...
bachelor thesis 2023
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Beekhuizen, Michael (author)
Cardiovascular diseases are one of the primary causes of mortality worldwide. Paroxysmal atrial fibrillation is a specific type that is difficult to detect and diagnose in a short time frame. To overcome this, we investigated if long-term wearable data can be used for the detection of heart diseases. The BigIdeasLab_STEP dataset and long-term...
master thesis 2023
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