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WHDL - 00011915

Training Data Selector

Gregory Smith

Resource Types

Academic (Thesis, Dissertation, Etc.)

Resource Languages

English

Institutional Repository

Description / Abstract

Submitted to the Department of Mathematics and Computer Science in partial fulfillment of the requirements for the degree of Bachelor of Science

Gathering training data for a pixel-based machine learning classifier can be a painstakingly slow and tedious task. Not only must the user ensure the data being gathered is accurate, but they must also gather enough data to successfully train the classifier. The Training Data Selector (TDS) allows a user to accurately and quickly produce training data. This tool provides accurate training data for analytics as diverse as wildland fire management and pathology. The TDS allows the user to draw on data in any web browser, label that data, and then extract and export the pixel data, thus allowing a classifer to learn what that picture is as well as images like it. This application utilizes human expertise without compromising computer processing power. As well as providing a quick and clean solution to extracting information from data to be used in various supervised classifiers, the TDS application was built and designed for users who are inexperienced with computer applications and therefore provides a simple, easy, and intuitive interface for all users on all platforms. The TDS provides the greatest flexibility, power, and availability to extract the selected data the user chooses for training a supervised classifier.