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Investigating Semantic Properties Of Images Generated From Natural Language Using Neural Networks, Samuel Ward Schrader

Boise State University Theses and Dissertations

This work explores the attributes, properties, and potential uses of generative neural networks within the realm of encoding semantics. It works toward answering the questions of: If one uses generative neural networks to create a picture based on natural language, does the resultant picture encode the text's semantics in a way a computer system can process? Could such a system be more precise than current solutions at detecting, measuring, or comparing semantic properties of generated images, and thus their source text, or their source semantics?

This work is undertaken in the hope that detecting previously unknown properties, or better understanding …