"machine learning" - Selaus asiasanan mukaan Kandidaatintutkielmat
Viitteet 21-40 / 70
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Deep Learning For Portfolio Optimization With Delta Controlled
(2022)
KandidaatintyöThe cryptocurrency market is considered high-risk compared to traditional investment channels such as stocks or bonds. The whole market trend is primarily affected by only a few top-of-the-market capitalization cryptocurrencies ... -
Deep Learning with Fourier Transformed Images
(2023)
KandidaatintyöThe research and applications based on deep learning have increased rapidly over the past years. Image classification is one of the main applicational scopes of deep learning. Many existing image classifiers are based on ... -
Deep open-domain chatbots: A study on the ParlAI Blended Skill Talk chatbot
(2021)
KandidaatintyöNatural language processing has seen many advancements in recent years due to the availability of large amounts of data and breakthroughs in deep learning. One evolving field of NLP is dialogue systems which are used for ... -
Differentiable Camera Model for Learning-Based Optimizations
(2021)
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Enhancing Audio Privacy with Representation Learning through Source Separation and Robust Adversarial Techniques
(2024)
KandidaatintyöThe significant rise in employing smart sensors and machine learning approaches in acoustic monitoring comes with speech privacy concerns during the data transmission from local devices to remote servers. This thesis ... -
Evaluating and predicting developers' contribution in software projects
(2021)
KandidaatintyöNowadays the software development industry is growing rapidly as well as the popularity of the distance work. Hence there are a lot of big software teams scattered all over the world and it might be very important for a ... -
Forecasting emergency department arrivals with neural networks
(2020)
KandidaatintyöEmergency departments often suffer from chronic overloading as well as seasonal spikes in number of arrivals. In this study three different Deep learning based models are used to try to predict the next days arrivals to ... -
Frequency Domain Image Classification with Convolutional Neural Networks
(2023)
KandidaatintyöThe purpose of this thesis was to explore image classification in the frequency domain using convolutional neural networks. Image classification is a common application of machine learning where image samples are categorized ... -
Gender gap in heart disease – differences in female and male biomechanics
(2023)
KandidaatintyöCardiovascular diseases are the leading cause of death worldwide, for both males and females. Still, sex differences are considered insignificant in treatment of heart disease, and the reasons behind the sex differences ... -
Harnessing neural networks for predicting next actions of investors
(2023)
KandidaatintyöThe goal of this study is to find out whether machine learning (ML) can be harnessed to predict next actions of active household investors. More precisely to compare the performance of three machine learning model structures. ... -
Image and Video Processing Methods for Studying hiPSC-derived Cardiomyocyte Biomechanics
(2023)
KandidaatintyöCardiovascular disease (CVD) is the most common cause of death globally. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) provide a suitable model for studying CVD and developing new treatments. Using ... -
Image classification in the Fourier domain
(2024)
KandidaatintyöArtificial intelligence (AI) has recently gained a lot of attention in the media. The main driving force for emerging AI tools such as ChatGPT has been deep learning enabled by modern computational hardware. Deep learning ... -
Impact of Dataset Size in Large Language Model-Based Food-Disease Relation Detection
(2024)
KandidaatintyöUnderstanding relations between nutrients and diseases is important for healthcare advice and public health policies. Large amounts of such information is available in different scientific papers, but it is not easily ... -
Implementing a speech-to-text module for a conversational avatar
(2021)
KandidaatintyöMachine learning, or more specifically deep learning, has been gaining more and more popularity in complex computer science applications. One of these is speech recognition, where speech is translated into text by a computer. ... -
Improving Code Quality Using Fine-tuning Large Language Models
(2024)
KandidaatintyöLarge language models has demonstrated significant capabilities in solving real-life problems by the means of generating human-like responses to input text in the similar format. However, these generic languages exhibit ... -
Incremental learning for audio event classification
(2025)
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Intermediate goal generation for off-policy reinforcement learning methods
(2022)
KandidaatintyöReinforcement learning is a branch of machine learning, which has seen increasing interest in the last few years. Reinforcement learning tries to teach an agent to complete a task in an optimal way. The optimality is defined ... -
Learned manipulation on robot arms with parallel-jaw grippers
(2023)
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Learning privacy-preserving representation of audio data with adversarial learning: The usage of adversarial learning to address privacy problems in smart audio processing devices
(2023)
KandidaatintyöRecently, the development of IoT leads to numerous automated machine listening systems be ing introduced. In the audio signals processed by these systems, human voice also exists, which poses a threat of leakage of privacy ...
