Searched for: subject%3A%22Attention%22
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van Osch, Millen (author)
Joint attention is the shared focus multiple people can have on the same object and it is subconsciously used by humans every day. The simple act of verbally or non-verbally pointing out an object to one another, is a form of joint attention. Its use facilitates human cooperation, such as when someone needs to hand over an object to another...
master thesis 2023
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Jiang, Haitao (author)
The technique of ultrasound-guided needle insertion is commonly employed in various clinical fields, including biopsy, anesthesia, brachytherapy, and ablation. However, the visibility of the needle in ultrasound (US) images remains a persistent challenge. To improve the guidance accuracy of needle insertion during interventions, it is crucial to...
master thesis 2023
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Naber, Titus (author)
master thesis 2023
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Mekkes, Erik (author)
Large Language Models of code have seen significant jumps in performance recently. However, these jumps tend to accompany a notable and perhaps concerning increase in scale and costs. We contribute an evaluation of prediction performance with respect to model size by assessing the layer-wise progression for language and user-defined elements in...
bachelor thesis 2023
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Keeler, Miranda (author)
We present an investigation into the relationship between the average depth of the first correct prediction and the performance of CodeGen. This was done on a dataset comprised of code files comprised of C++, Go, Java, Julia, Kotlin, and Python. The analysis involved investigating the model's predictions at different layers using a Tuned Lens,...
bachelor thesis 2023
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Kuo, Nadine (author)
The development of contemporary source code auto-completion tools have significantly boosted productivity and efficiency of developers. In 2021, the GPT-2-based Transformer CodeGPT was developed to support code completion and text-to-code generation. Similarly to most code models however, CodeGPT was trained on a limited set of widely-used...
bachelor thesis 2023
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Popescu, Popescu (author)
In recent years, deep learning techniques, particularly transformer models, have demonstrated remarkable advancements in the accuracy and efficiency of language models. These models provide the foundation for many natural language processing tasks, including code completion. The effectiveness of code completion models has been the subject of a...
bachelor thesis 2023
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Gielisse, A.S. (author)
Most recent works on optical flow use convex upsampling as the last step to obtain high-resolution flow. In this work, we show and discuss several issues and limitations of this currently widely adopted convex upsampling approach. We propose a series of changes, inspired by the observation that convex upsampling as currently implemented performs...
master thesis 2023
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Bakay, Ahmed (author)
Human operators who are tasked with monitoring automation systems may experience a high visual demand to process the information streams from these systems. The visual sampling behavior of human operators can be described using mathematical models. These models can help designers improve environments where multiple signals are present for human...
master thesis 2022
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Collé, Baptiste (author)
Most deep learning models fail to generalize in production. Indeed, sometimes data used during training does not completely reflect the deployed environment. The test data is then considered out-of-distribution compared to the training data. In this paper, we focus on out-of-distribution performance for image classification. In fact,...
bachelor thesis 2022
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de Vries, Yorick (author)
With the increasing global demand for logistics, supply chains have grown a lot in volume over the last decades. To be able to operate effectively within the capacity constraints of the carriers, proper collaboration and optimization of order allocation is required. Van Berkel Logistics facilitates the transport of containers by trucks from sea...
master thesis 2021
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Alfieri, Andrea (author)
Transformers can generate predictions auto-regressively by conditioning each sequence element on the previous ones, or can produce output sequences in parallel. While research has mostly explored upon this difference on tasks that are sequential in nature, we study this contrast on visual set prediction tasks, to analyze the core behaviour of...
master thesis 2021
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van Diepen, Aaron (author)
Recurrent neural networks (RNNs) used in time series prediction are still not perfect in their predictions and improvements can still be made in the area. Most recently transformers have led to great improvements in the field of RNNs, however transformers can not be used on time series data, because the architecture of transformers does not...
bachelor thesis 2021
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Şen, Sina (author)
The introduction of Attention Long Short Term Memory (ALSTM) produces an alternative to Long Short Term Memory (LSTM) by aiming to optimize information passing via removing the complexity of the cells in LSTM. In this work, the results and comparison of the performance of LSTM algorithms versus ALSTM architectures are assessed through the...
bachelor thesis 2021
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Wang, Mingshi (author)
According to the development of data-related techniques, aimed at exploring the largest value of data, price prediction has been seen as more vital for quantifying and pricing stock. To solve this problem, the learning based algorithm became popular during modern computing techniques development. LSTM (Long Short-Term Memory) techniques attract...
bachelor thesis 2021
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Pronk, Jeffrey (author)
In this research, a learner’s sustained attention in the remote learning context will be studied by collecting data from different sensors. By combining the results of these sensors in a multi-modal analytics tool, the estimation of the learner’s sustained attention can hopefully be improved. This research will mainly focus on microphone...
bachelor thesis 2021
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Den Toonder, Jurriaan (author)
Remote learning, learning from home using online available materials, is becoming increasingly more common. This paper focuses on reading activities during remote learning. An important part of learning is keeping sustained attention on the learning materials, as a shift from sustained attention to internal thought or mind-wandering oftentimes...
bachelor thesis 2021
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Eijssen, Dirk (author)
Background: Automated vehicles are promoted as a safety improvement, but they may also bring a new problem of ‘out of the loop’ errors. Automation support in the form of gaze-contingent feedback might be the solution for these errors. Using the SEEV model, operator’s attention allocation can be predicted and using live gaze data, the driver’s...
master thesis 2021
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Remmerswaal, Leonie (author)
The amount of people working from home has been increasing. However, working from home has its issues and consequences. The degree to which one experiences recovery from stress and fatigue is limited when working from home, which has consequences on motivation, performance, health, and well-being. The aim of this project was...
master thesis 2021
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Tomy, Abhishek (author)
A human driver can gauge the intention and signals given by other road users indicative of their future behaviour. The intentions and signals are identified by looking at the cues originating from vulnerable road users or their surroundings (hand signals, head orientation, posture, traffic signals, distance to curb, etc.). Taking all these cues...
master thesis 2020
Searched for: subject%3A%22Attention%22
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