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Type-1 and type-2 fuzzy systems for detecting visitors in an uncertain environment
(University of Missouri--Columbia, 2009)
In this work, I have developed an algorithm to detect the presence of visitors in a noninvasive manner. This algorithm is designed as part of an in home monitoring system. The data from the algorithm will be used as a way ...
Pixel level pavement crack detection using deep convolutional neural network with residual blocks
(University of Missouri--Columbia, 2019)
Road condition monitoring, such as surface defects and pavement cracks detection, is an important task in road management. Automated road surface defect detection is also a challenging problem in computer vision and machine ...
Human-assisted self-supervised labeling of large data sets
(University of Missouri--Columbia, 2022)
There is a severe demand for, and shortage of, large accurately labeled datasets to train supervised computational intelligence (CI) algorithms in domains like unmanned aerial systems (UAS) and autonomous vehicles. This ...