Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 11 of 11 for “"Vélrænt nám"”.
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Vélfugl : grunnur að vélrænu námi til flugstýringar
Í þessu verkefni var lagður grunnur að vélrænu námi fyrir flugstýringu vélfugls í samstarfi við Flygildi ehf. Markmið verkefnisins var að hanna og smíða prófunarumhverfi þar sem hægt væri að stjórna vænghreyfingum vélfugls með servómótorum, mæla krafta sem myndast við hreyfingarnar og nota …
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Named entity recognition for Icelandic: comparing and combining different machine learning methods
Named Entity Recognition (NER) is the task of identifying person names, places, organizations, and other Named Entities in text. This can also include some numerical entities like dates, amounts of money and percentages. NER is often an important step in other Natural Language Processing tasks, …
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Representation learning for multivariate time series : artefact analysis on sleep recordings
The application of machine learning is becoming a major area of interest within the field of sleep science. The domain of sleep science is shifting, due to the automation machine learning introduces. Automatic analyses are vital to minimise diagnostic time and provide as many people as possible …
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Performance of an AGI-aspiring system & narrow-AI approaches : a systematic comparison
While research progresses in artificial general intelligence (AGI), as well as in traditional narrow-AI such as machine learning algorithms, direct comparisons between AI learners are few and far between. Evaluating and comparing the performance of different architectures is likely to prove …
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Utilizing machine learning techniques in estimating ankle prosthesis power output using wearable IMU sensors
Ankle power output can be used to identify abnormalities and uneven weight distribution in gait. The acquring of the ankle power output usually involves using invasive motion capture systems along with force plates to capture the exerted power on the ground during stance phase. When clinicians are …
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Radar Integration into Power Knee
Markmið verkefnisins er að innleiða ratsjá inn í Power Knee. Verkefnið samanstendur af val á ratsjá, hönnun á prentplötu sem passar í núverandi vöru og þróun á hugbúnaði.
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Evaluating knowledge transferability in chess endgames using deep neural networks
Transfer learning is becoming an essential part of modern machine learning, especially in the field of deep neural networks. In the domain of image recognition there are known methods to evaluate the transferability of features which are based on evaluating to what degree a feature extractor can be …
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Predicting football match outcomes with fantasy league data and deep learning
Predicting and betting on the outcome of football matches has been around as long as the game itself. However, with the explosion of online betting over the past 15 years, the stakes are much higher, and the person who accurately predicts the outcome has a chance of making sizable profits. With …
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Predicting Passenger Demand and Optimizing Fleet Allocation: A Machine Learning Approach for Icelandic Tour Operators
The need for more efficient resource allocation methods in tour operations has been created by the growing complexity driven by increasing tourism in destinations like Iceland. In this study, the application of machine learning techniques to optimize tour operations through improved passenger …
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A machine learning approach to gait cycle classification for Rheo 3 low-end torque failure
This study aims to assess the feasibility of employing machine learning algorithms to classify low-end torque failure in Rheo 3 prosthetic knees to find a reliable way of diagnosing this fault in real-world scenarios, considering that in most cases, this malfunction typically goes unnoticed by the …
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Virtual humans making first contact : teaching socially appropriate approaching behavior using deep reinforcement learning
Socially appropriate behavior of humans in public places is governed by various factors and rules. While these aspects have been previously well-explored for virtual humans engaged in focused interactions (e.g. conversations), the same is not true for unfocused interactions (e.g. merely being …