Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 3 of 3
Full-Text Articles in Entire DC Network
Integrated Data Fusion And Mining (Idfm) Technique For Monitoring Water Quality In Large And Small Lakes, Benjamin Vannah
Integrated Data Fusion And Mining (Idfm) Technique For Monitoring Water Quality In Large And Small Lakes, Benjamin Vannah
Electronic Theses and Dissertations
Monitoring water quality on a near-real-time basis to address water resources management and public health concerns in coupled natural systems and the built environment is by no means an easy task. Furthermore, this emerging societal challenge will continue to grow, due to the ever-increasing anthropogenic impacts upon surface waters. For example, urban growth and agricultural operations have led to an influx of nutrients into surface waters stimulating harmful algal bloom formation, and stormwater runoff from urban areas contributes to the accumulation of total organic carbon (TOC) in surface waters. TOC in surface waters is a known precursor of disinfection byproducts …
Life Long Learning In Sparse Learning Environments, John Reeder
Life Long Learning In Sparse Learning Environments, John Reeder
Electronic Theses and Dissertations
Life long learning is a machine learning technique that deals with learning sequential tasks over time. It seeks to transfer knowledge from previous learning tasks to new learning tasks in order to increase generalization performance and learning speed. Real-time learning environments in which many agents are participating may provide learning opportunities but they are spread out in time and space outside of the geographical scope of a single learning agent. This research seeks to provide an algorithm and framework for life long learning among a network of agents in a sparse real-time learning environment. This work will utilize the robust …
Human Action Localization And Recognition In Unconstrained Videos, Hakan Boyraz
Human Action Localization And Recognition In Unconstrained Videos, Hakan Boyraz
Electronic Theses and Dissertations
As imaging systems become ubiquitous, the ability to recognize human actions is becoming increasingly important. Just as in the object detection and recognition literature, action recognition can be roughly divided into classification tasks, where the goal is to classify a video according to the action depicted in the video, and detection tasks, where the goal is to detect and localize a human performing a particular action. A growing literature is demonstrating the benefits of localizing discriminative sub-regions of images and videos when performing recognition tasks. In this thesis, we address the action detection and recognition problems. Action detection in video …