… attributed to the false detection of coronal holes. Our interest in this study thus lies in avoiding
the false detection of coronal holes, that is, to classify a filament as a coronal hole. On the …

… In supervised classification problems, an object is observed and we aim to classify it into …
When applying the developed algorithms in the form of an automated coronal hole detection …

… This paper introduces the usage of semi-supervised learning to obtain competitive detection
accuracy of measuring drilled holes on composite parts with very limited noisy training data. …

… This study aims to conduct abnormality detection by applying machine learning algorithms
when drilling a carbon fiber reinforced plastic laminate. In-process signals including current, …

… The possibility of using naive Bayes classifiers for supervised classification of contact …
The main reason for studying wood hole-defects is that these sorts of damage are aimed to …

… supervised classification to the problem of lithology reconstruction from FMS borehole wall
images acquired in ODP Hole … In particular, the detection rate of small massive rock intervals …

… Detection techniques based on deep learning with RGB-D semantic segmentation have …
equipment to detect blast-holes, this paper extends the core idea of semi-supervised learning to …

… morphological operators and supervised classification. It can … the detection and classification
steps: (i) an improved object … We assume that this hole can be filled at that level because …

… A simple Coverage Hole (CH) may degrade the performance and the reputation of any …
detection from mobile network data. Therefore, we present a method by utilising Semi‑Supervised …

… CT scan images into clear wood, background, knots, rot and holes using 2-D … detection
accuracy, no marked difference could be established between such supervised classification al…