Engineering Commons^™

Computer Vision-Based Automatic Railroad Crossing Monitoring And Track Inspection, Feng Guo

Theses and Dissertations

Currently, there are many imminent challenges in the railroad infrastructure system of the United States, impacting the operation, safety, and management of railroad transportation. In this work, three major challenges which are overcrowded traffic congestion at the grade crossing, low-efficiency and accuracy on inspection of missing or broken rail track components, and dense rail surface defects without quantification, respectively are studied. The congested railroad grade crossing not only introduces significant traffic delays to travelers but also brings potential safety concerns to the first responders. However, limited studies have been devoted on developing an intelligent traffic monitoring system which is significant …

Sensor Fusion For Object Detection And Tracking In Autonomous Vehicles, Mohamad Ramin Nabati

Doctoral Dissertations

Autonomous driving vehicles depend on their perception system to understand the environment and identify all static and dynamic obstacles surrounding the vehicle. The perception system in an autonomous vehicle uses the sensory data obtained from different sensor modalities to understand the environment and perform a variety of tasks such as object detection and object tracking. Combining the outputs of different sensors to obtain a more reliable and robust outcome is called sensor fusion. This dissertation studies the problem of sensor fusion for object detection and object tracking in autonomous driving vehicles and explores different approaches for utilizing deep neural networks …

Automating Deep-Sea Video Annotation, Hanson Egbert

Master's Theses

As the world explores opportunities to develop offshore renewable energy capacity, there will be a growing need for pre-construction biological surveys and post-construction monitoring in the challenging marine environment. Underwater video is a powerful tool to facilitate such surveys, but the interpretation of the imagery is costly and time-consuming. Emerging technologies have improved automated analysis of underwater video, but these technologies are not yet accurate or accessible enough for widespread adoption in the scientific community or industries that might benefit from these tools.

To address these challenges, prior research developed a website that allows to: (1) Quickly play and annotate …

Bibliometric Analysis On Optimal Path Planning For Robots, Varad Sandeep Nerlekar, Tathaagat Nihar Mamtura, Nishant Singh, Suket Anand, Sushma Parihar

Library Philosophy and Practice (e-journal)

Traversing from a given point to another while avoiding collision with obstacles is one of the key goals of path planning for robots [1]. Doing so in the most optimal way - the minimum total distance traveled by the robot is the objective of our study [2,3]. To do so, the algorithms implemented on the robots need to constantly map the environment or workspace in real time and subsequently create paths for the traversal in the environment without colliding with objects or obstacles [4,5]. Throughout the years, many researchers have conducted their own studies, researches and have proposed approaches for …

Assessment And Diagnosis Of Human Colorectal And Ovarian Cancer Using Optical Imaging And Computer-Aided Diagnosis, Yifeng Zeng

McKelvey School of Engineering Theses & Dissertations

Tissue optical scattering has recently emerged as an important diagnosis parameter associated with early tumor development and progression. To characterize the differences between benign and malignant colorectal tissues, we have created an automated optical scattering coefficient mapping algorithm using an optical coherence tomography (OCT) system. A novel feature called the angular spectrum index quantifies the scattering coefficient distribution. In addition to scattering, subsurface morphological changes are also associated with the development of colorectal cancer. We have observed a specific mucosa structure indicating normal human colorectal tissue, and have developed a real-time pattern recognition neural network to localize this specific structure …