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Curvilinear segmentation and classification of blood vessels using random forest and deep learning
(University of Missouri--Columbia, 2020)
Curvilinear structures occur in many biomedical imagery, and reliable segmentation and classification is crucial for automatic image analysis. In this dissertation, we consider optimized filter bank (OFB) features with ...
Analysis of flame images in gas-fired furnaces
(University of Missouri--Columbia, 2007)
A promising architecture is proposed in this research work for evaluating gasfired furnace flame combustion quality. The quality assessment is based on information on its fuel and oxidizer flow rate level which are the ...
Selected techniques for vehicle tracking and assessment in wide area motion imagery
(University of Missouri--Columbia, 2010)
of square miles), and with very minimal ground resolution (images taken at about 4000ft to 5000ft above ground) and with low frame rates (1-10 frames/ sec), is a very challenging job. This research describes some of the techniques and approaches taken...
Local and deep texture features for classification of natural and biomedical images
(University of Missouri--Columbia, 2019)
Developing efficient feature descriptors is very important in many computer vision applications including biomedical image analysis. In the past two decades and before the popularity of deep learning approaches in image ...