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Time series clustering by extracted features
(2019)
Clustering electricity consumers can give insight into how a particular consumption profile is related to other attributes of the customer, for example the residence size or whether a sauna is in use or not. Furthermore, ...
Improving the performance of Bayesian deep model training for artery-vein segmentation
(2020)
Retinal images are an important tool for diagnosis of ocular diseases. Automating the process of screening the retinal images would allow wider screening and make diagnosing of patients’ swifter. The possibility of performing ...
Plankton image clustering using similarity metric learning
(2022)
Technological advancement has evolved the imaging equipment used in plankton imaging. Nowadays it is possible to take images more efficiently. Due to the increased amount of images the processing time is longer. The ...
Classifying customer companies in an enterprise resource planning system using machine learning methods
(2022)
Information systems such as smart phone applications collect large amounts of data about their users. The data is used mostly for the system’s primary task, but machine learning methods can be used to get additional value ...
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 ...