Detection Of Roof Boundaries Using Lidar Data And Aerial Photography,
2010
University of Kentucky
Detection Of Roof Boundaries Using Lidar Data And Aerial Photography, Andrew David Gombos
University of Kentucky Master's Theses
The recent growth in inexpensive laser scanning sensors has created entire fields of research aimed at processing this data. One application is determining the polygonal boundaries of roofs, as seen from an overhead view. The resulting building outlines have many commercial as well as military applications. My work in this area has created a segmentation algorithm where the descriptive features are computationally and theoretically simpler than previous methods. A support vector machine is used to segment data points using these features, and their use is not common for roof detection to date. Despite the simplicity of the feature calculations, the …
Automatic Detection Of Malignant Melanoma Using Boundary Gradient Information In Dermoscopy Images,
2010
Missouri University of Science and Technology
Automatic Detection Of Malignant Melanoma Using Boundary Gradient Information In Dermoscopy Images, Yogesh Ajit Dandekar
Masters Theses
"This thesis demonstrates an algorithm which uses local border features, primarily derived from the border gradient, to help determine whether the lesion is a malignant melanoma or a benign lesion. Although this algorithm uses manually-marked lesion borders, it could be included in a fully automatic routine. A Prewitt algorithm with a window size proportional to the area of the lesion is used to calculate the gradient over the entire lesion boundary. This gradient value is used to calculate various boundary features, such as mean, standard deviation, and direction of maximum gradient. The dark and white areas inside the lesion combined …
Adaptive Resource Allocation For Cognitive Wireless Ad Hoc Networks,
2010
Missouri University of Science and Technology
Adaptive Resource Allocation For Cognitive Wireless Ad Hoc Networks, Behdis Eslamnour
Doctoral Dissertations
"Widespread use of resource constrained wireless ad hoc networks requires careful management of the network resources in order to maximize the utilization. In cognitive wireless networks, resources such as spectrum, energy, communication links/paths, time, space, modulation scheme, have to be managed to maintain quality of service (QoS). Therefore in the first paper, a distributed dynamic channel allocation scheme is proposed for multi-channel wireless ad hoc networks with single-radio nodes. The proposed learning scheme adapts the probabilities of selecting each channel as a function of the error in the performance index at each step.
Due to frequent changes in topology and …
