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Full-Text Articles in Engineering
Optical Flow-Based Odometry For Underground Tunnel Exploration, Terra Kier
Optical Flow-Based Odometry For Underground Tunnel Exploration, Terra Kier
Theses and Dissertations
As military operations in degraded or GPS-denied environments continue to increase in frequency and importance, there is an increased necessity to be able to determine precision location within these environments. Furthermore, authorities are finding a record number of tunnels along the U.S.-Mexico border; therefore, underground tunnel characterization is becoming a high priority for U.S. Homeland Security as well. This thesis investigates the performance of a new image registration technique based on a two camera optical- flow configuration using phase correlation techniques. These techniques differ from other image based navigation methods but present a viable alternative increasing autonomy and answering the …
Overcoming Pose Limitations Of A Skin-Cued Histograms Of Oriented Gradients Dismount Detector Through Contextual Use Of Skin Islands And Multiple Support Vector Machines, Jonathon R. Climer
Overcoming Pose Limitations Of A Skin-Cued Histograms Of Oriented Gradients Dismount Detector Through Contextual Use Of Skin Islands And Multiple Support Vector Machines, Jonathon R. Climer
Theses and Dissertations
This thesis provides a novel visualization method to analyze the impact that articulations in dismount pose and camera aspect angle have on histograms of oriented gradients (HOG) features and eventual detections. Insights from these relationships are used to identify limitations in a state of the art skin cued HOG dismount detector's ability to detect poses not in a standard upright stances. Improvements to detector performance are made by further leveraging available skin information, reducing false detections by an additional order of magnitude. In addition, a method is outlined for training supplemental support vector machines (SVMs) from computer generated data, for …
A Multi Agent System For Flow-Based Intrusion Detection Using Reputation And Evolutionary Computation, David Hancock
A Multi Agent System For Flow-Based Intrusion Detection Using Reputation And Evolutionary Computation, David Hancock
Theses and Dissertations
The rising sophistication of cyber threats as well as the improvement of physical computer network properties present increasing challenges to contemporary Intrusion Detection (ID) techniques. To respond to these challenges, a multi agent system (MAS) coupled with flow-based ID techniques may effectively complement traditional ID systems. This paper develops: 1) a scalable software architecture for a new, self-organized, multi agent, flow-based ID system; and 2) a network simulation environment suitable for evaluating implementations of this MAS architecture and for other research purposes. Self-organization is achieved via 1) a reputation system that influences agent mobility in the search for effective vantage …
Holistic Network Defense: Fusing Host And Network Features For Attack Classification, Jenny W. Ji
Holistic Network Defense: Fusing Host And Network Features For Attack Classification, Jenny W. Ji
Theses and Dissertations
This work presents a hybrid network-host monitoring strategy, which fuses data from both the network and the host to recognize malware infections. This work focuses on three categories: Normal, Scanning, and Infected. The network-host sensor fusion is accomplished by extracting 248 features from network traffic using the Fullstats Network Feature generator and from the host using text mining, looking at the frequency of the 500 most common strings and analyzing them as word vectors. Improvements to detection performance are made by synergistically fusing network features obtained from IP packet flows and host features, obtained from text mining port, processor, logon …
Kernelized Locality-Sensitive Hashing For Fast Image Landmark Association, Mark A. Weems
Kernelized Locality-Sensitive Hashing For Fast Image Landmark Association, Mark A. Weems
Theses and Dissertations
As the concept of war has evolved, navigation in urban environments where GPS may be degraded is increasingly becoming more important. Two existing solutions are vision-aided navigation and vision-based Simultaneous Localization and Mapping (SLAM). The problem, however, is that vision-based navigation techniques can require excessive amounts of memory and increased computational complexity resulting in a decrease in speed. This research focuses on techniques to improve such issues by speeding up and optimizing the data association process in vision-based SLAM. Specifically, this work studies the current methods that algorithms use to associate a current robot pose to that of one previously …