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Deep Convolutional Neural Networks for MultilabelPrediction Using RGBD Data
Robotics relies heavily on the system's ability to perceive the world around the robot accurately and quickly. In a narrow setting as in manufacturing this goal is relatively simple. To make robotics feasible in more ...
Anomalous Motion Detection of Vehicles on Highway using Deep Learning
Research in visual anomaly detection draws much interest due to applications in surveillance. Common data sets for evaluation are constructed using a stationary camera overlooking an area of interest. Despite the challenges ...
PATIENT CLASSIFICATION USING DEEP LEARNING
With diseases like Alzheimer's and Influenza still claiming lives, there have been a lot of methods developed in order to combat these diseases. There is a possibility that the key to finding susceptibility towards a disease ...
Solutions for Improving Model Simulation in the Virtual Watershed Platform
This thesis is a collage of the works implemented to enhance the modeling capabilities of the NSF EPSCoR-supported Western Consortium for Water Analysis, Visualization and Exploration (WC-WAVE) Virtual Watershed Project. ...
Clinical Dataset Analysis and Patient Outcome Prediction via Machine Learning
We analyze and evaluate relevant machine learning methods for use in extract-ing and understanding clinical data sets in the context of optimization ofclinical processes. Three data sets were considered to demonstrate the ...
Predicting Agent Behavior by Estimating Motion Planners
To navigate the world safely, autonomous agents must predict the future actions of the other agents in the world. We propose a method to estimate the future positions of other agents by using a sample-based planner that ...