Browsing College of Engineering and Informatics by Subject "machine learning"
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Image-based classification of bladder state using electrical impedance tomography
(IOP Publishing, 2018-12-03)Objective: In this study, we examine the potential of using machine learning classification to determine the bladder state ( not full , full ) with electrical impedance tomography (EIT) images of the pelvic region. Accurate ... -
Species mixing proportion and aridity influence in the height–diameter relationship for different species mixtures in Mediterranean forests
(MDPI, 2022-01-14)Estimating tree height is essential for modelling and managing both pure and mixed forest stands. Although height–diameter (H–D) relationships have been traditionally fitted for pure stands, attention must be paid when ...