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Plankton recognition from imaging flow cytometer data using convolutional neural networks
(2018)
Research on plankton populations is bottlenecked by the ability to obtain species-level information within a required time frame. Recent technological advances in imaging hardware have made it possible to obtain large ...
Filter method for feature selection using fuzziness index number with fuzzy k-nearest neighbor classifier
(2020)
The extensive data sets of real-world contain high-dimensional information; among them, some may hold irrelevant information that complicates the data set. Feature selection is regarded as a useful data preprocessing ...
Semi-supervised learning for plankton image classification
(2020)
The production of big data from plankton populations has become feasible with the use of imaging devices. This opens up the possibility of testing key characteristics in planktonic systems. The manual labeling of images ...
Investigating the impact of Brexit on the exchange rate volatility of the pound sterling with respect to the Euro and the US dollar
(2020)
This thesis investigates did Brexit affect on the exchange rate volatility of the British pound sterling towards the Euro (GBP/EUR) and towards the U.S. dollar (GBP/USD). The observed time frame is from January 2011 to ...
Material classification in the industry
(2023)
In the industry material classification and quality control are key challenges that require speed and accuracy. Automation of material classification using machine learning classifiers would provide a unified method that ...
Similarity measurements for rapakivi granite using soft independent modelling of class analogy and metric learning
(2022)
Rapakivi granite from south-eastern Finland has been used in many buildings in the historic centre of Saint Petersburg, Russia. Due to weathering and breakdown, the building stones will need to be replaced from time to ...
Statistical quality control via machine learning
(2023)
Faults in the rolling element bearings are a common problem in rotating equipment. Therefore predicting and identifying the faults from vibration signals has gained increased attention. The goal of this thesis is to explore ...