"machine learning" - Selaus asiasanan mukaan Kandidaatintutkielmat
Viitteet 1-20 / 68
-
Acoustic Scene Classification with Interpretable Deep Neural Networks
(2024)
KandidaatintyöEnvironmental sounds are an important source of information, yet one that our devices commonly underutilize. While this has started to change in recent years with the growing interest in acoustic scene classification (ASC) ... -
Acoustic Scene Classification With L3 Embeddings: Transfer learning experiment
(2020)
KandidaatintyöCountless audio data are recorded on a daily basis in different environments. Being able to recognize the context of the audio automatically would be beneficial in many context-aware systems such as hearing aids and ... -
AI in simulated quadrupeds
(2024)
Kandidaatintyö -
AI-Based Object Recognition on RGBD Camera Images
(2020)
KandidaatintyöIn this thesis, it was researched how RGBD camera images could be implemented in object recognition algorithms and how they affect the performance of the algorithm. In the beginning, the history of artificial intelligence, ... -
AI-Driven Approaches to Product Feature Prioritization
(2024)
KandidaatintyöCompanies developing technology products must decide which product features to include in their product releases. These decisions must consider customer requirements, the feature's value and cost, and the release schedule. ... -
Assessing the time efficiency of a novel implementation of Short-time Fourier transform using graphics processing units
(2020)
KandidaatintyöIn the ever growing field of machine learning more and more efficient information retrieval methods are in demand as more data needs to be processed. In the audio related machine learning short-time Fourier transform is ... -
Automated classification of cardiac arrhythmias using ECG signals
(2025)
KandidaatintyöHeart and vascular diseases are nowadays the leading cause of death globally and their identification and treatment at an early stage are important for preventing deaths. In this thesis the research is about the accuracy ... -
Automatic Assessment Of Parkinson’s Disease Using Spontaneous Speech
(2023)
KandidaatintyöParkinson's disease is a neurodegenerative disease with a range of symptoms, including speech impairments. These can be detected with digital signal processing, since speech signals carry paralinguistic information, which ... -
Automatic syllable count estimation from speech using neural network trained with a dsp-based estimator
(2023)
Valinnaisten aineopintojen tutkielmaAccurate syllable count estimation is crucial in various speech-related applications such as speech rate and rhythm analysis or language development research. However, it remains a challenging task to find cost-effective ... -
Automatic Text Generation Using Supervised Pre-training and Reinforcement Learning Based Adaptation
(2021)
KandidaatintyöText generation tasks are becoming more and more prominent in applications such as machine translation, image captioning, dialogue systems, etc. While text generation systems often require an extremely large amount of data, ... -
Co-simulation using Python and Simulink
(2024)
KandidaatintyöCo-simulation is a methodology of computer analysis and simulation. This technique involves different kinds of specialized simulation programs interacting and working simultaneously to reach more comprehensive results ... -
Comparative analysis of Neural Implicit Representation Methods for 3D Reconstruction
(2024)
KandidaatintyöIn recent years, advancements in artificial intelligence, robotics, augmented reality, and virtual reality have increased the volume of research that is done on one of the most intriguing topics in the field of computer ... -
Comparison of predictive models for time series forecasting : Power demand prediction of DC charging network
(2024)
KandidaatintyöThe widespread adoption of electric vehicles has made DC charging networks a crucial part of the infrastructure. These networks experience fluctuating power requirements influenced by factors such as traffic patterns and ... -
Cross-modal semantic retrieval in neural models of visually grounded speech
(2023)
KandidaatintyöMachine learning and its subset deep learning have been hot topics of technology for some years now. Visually grounded speech (VGS) models belong to a family of weakly supervised deep learning methods. The objective of VGS ... -
Data Acquisition for Forestry Scenes
(2023)
KandidaatintyöLarge quantities of samples are needed to train and benchmark today's data-driven machine-learning algorithms. Such well-established datasets for forestry scenes are scarce. This bachelor's thesis presents a simple, ... -
Datatieteen hyödyntäminen P2P-lainapäätöksissä
(2022)
Kandidaatintyö -
Dead reckoning with imu sensors : State-of-the-art
(2022)
Kandidaatintyö -
Deep face detection for interactive avatar
(2021)
KandidaatintyöFace detection is one of the most studied problems of the computer vision field. It is usually the first step for other face related technologies such as face recognition and verification. In this thesis, a face detection ... -
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 ...
