All ETDs from UAB

Advisory Committee Chair

Leon Jololian

Advisory Committee Members

Frank M Skidmore

Despina Stavrinos

Document Type

Thesis

Date of Award

2019

Degree Name by School

Master of Science in Electrical Engineering (MSEE) School of Engineering

Abstract

This paper aims to investigate the use of unsupervised saliency proposals in extracting suitable prior information from computed tomography scans of the head using image-level labels. The weak supervision learning method obtains useful information about an object’s location and fuses this result with an unsupervised saliency proposal to propagate labels to all related pixels. However, it is shown that unsupervised saliency guidance fails to supply the synthetic annotations with enough coherence to produce suitable segmentation.

Included in

Engineering Commons

Share

COinS