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Systems And Methods For Scalable Retinal Screening Programs, Jeremy Richard Benson
Systems And Methods For Scalable Retinal Screening Programs, Jeremy Richard Benson
Computer Science ETDs
This dissertation addresses gaps in artificial intelligence-based computer vision tasks in the medical image processing field. We demonstrate effective methods for standardizing and augmenting digital fundus photographs so that robust convolutional neural network-based systems can perform high-throughput disease classification and generalize to never-before-seen data from novel camera technologies, scaling with the changing hardware landscape, as well as keeping up with vast amount of incoming data from the ever-increasing population. We also tackle the problem of discovering relevant samples in an unlabeled cohort of image data, thus widening the bottleneck to all downstream supervised machine learning tasks.
Cognizant Composites: Seamless Integration Of Circuitry And Sensors Into Structural Composites, Reuben Fresquez
Cognizant Composites: Seamless Integration Of Circuitry And Sensors Into Structural Composites, Reuben Fresquez
Computer Science ETDs
This thesis describes a set of novel techniques for embedding sensors, circuitry, and electronics into structural composites. I leverage recent developments in human computer interaction to create sensors and circuitry that are seamlessly incorporated into structural composites. I fabricate bend and compression sensors, along with circuitry, from textiles, which enables me to add electronic capabilities without impacting the composite’s structural integrity. I describe the construction of these “cognizant composites” and demonstrate their functionality. I also explore techniques for embedding standard electronic components, including microcontrollers, into structural composites. Potential applications of this technology include buildings that can warn occupants if load-bearing …