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Application of deep convolutional neural networks to automatic feature/object detection in high resolution remote sensing imagery
(University of Missouri--Columbia, 2017)
of CaffeNet, GoogLeNet, ResNet-50, ResNet-101, on this data set. ResNet-101 achieved a 96.4 percent average accuracy on the world-wide SAM site data set. Finally, we present a China SAM site search and detection case study. First, we compare a visual Broad...
Vehicle license plate detection and recognition
(University of Missouri--Columbia, 2010)
In this work, we develop a license plate detection and recognition method using a SVM (Support Vector Machine) classifier with HOG (Histogram of Oriented Gradients) features. The system performs window searching at different ...