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Robust Multi-Class Decision Trees
(2021)
Diplomityö
Diplomityö
As machine learning is getting deployed more and more in security critical applications, the subject of robustness of machine learning algorithms, i.e. how vulnerable a given algorithm is to inputs that are designed to ...
Dynamic Topic Modeling and Clustering : Dynamic Topic Modeling and Clustering of Occupational Health and Safety Publications
(2022)
Pro gradu -tutkielma
Pro gradu -tutkielma
In recent years, natural language processing has advanced by creating new ways of modeling text using deep neural networks. These new models have demonstrated state of-the-art performance in several natural language ...
A Scalable Method for Nonlinear Dimensionality Reduction with Applications to Single-Cell Data
(2022)
Diplomityö
Diplomityö
Current generation biological measurement technologies enable quantifying cellular characteristics and processes at a genome-wide scale and single-cell resolution, producing invaluable data for research on complex phenomena ...
Estimating 6D pose of an object using RGB data
(2022)
Diplomityö
Diplomityö
Estimating object’s 6D pose is an important aspect of automating even complicated processes, especially in a field of robotics where information about object’s 6D pose can be used for manipulating objects with a robot. In ...
Feature Engineering in Condition-based Maintenance: A Case Study
(2022)
Diplomityö
Diplomityö
Advances in machine learning have paved the way for new data-centric approaches in the field of prognostics and health management of industrial applications. These approaches can help reduce the cost of system maintenance ...
Image coding for machines : Deep learning based post-processing filters
(2021)
Diplomityö
Diplomityö
Machine vision tasks such as object detection and instance segmentation are becoming more and more popular these days due to the quickly increasing performance of deep neural networks. Consequently, more and more multimedia ...
Predictability of One-Dimensional Dislocation Systems
(2020)
Diplomityö
Diplomityö
Automated machine learning: Evaluating AutoML frameworks
(2021)
Diplomityö
Diplomityö
Custom Object Detection with Deep Learning and Synthetic Datasets
(2021)
Diplomityö
Diplomityö
Detecting and localizing tree trunks is a necessary component for automatic harvesting machines. This task can be split into two sub-tasks: object detection and depth estimation. Object detection is a crucial problem that ...
Applying Machine Learning Algorithms to Psychiatric Patient Data
(2021)
Pro gradu -tutkielma
Pro gradu -tutkielma
The purpose of this work is to classify data in the field of psychiatry and neurology by applying different supervised machine learning algorithms.
The work is divided into two parts. The methodogical part represents all ...