Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Institution
Articles 1 - 2 of 2
Full-Text Articles in Physical Sciences and Mathematics
Using Deep Neural Networks To Classify Astronomical Images, Andrew D. Macpherson
Using Deep Neural Networks To Classify Astronomical Images, Andrew D. Macpherson
Honors Projects
As the quantity of astronomical data available continues to exceed the resources available for analysis, recent advances in artificial intelligence encourage the development of automated classification tools. This paper lays out a framework for constructing a deep neural network capable of classifying individual astronomical images by describing techniques to extract and label these objects from large images.
Teaching Computers To Teach Themselves: Synthesizing Training Data Based On Human-Perceived Elements, James Little
Teaching Computers To Teach Themselves: Synthesizing Training Data Based On Human-Perceived Elements, James Little
Honors Projects
Isolation-Based Scene Generation (IBSG) is a process for creating synthetic datasets made to train machine learning detectors and classifiers. In this project, we formalize the IBSG process and describe the scenarios—object detection and object classification given audio or image input—in which it can be useful. We then look at the Stanford Street View House Number (SVHN) dataset and build several different IBSG training datasets based on existing SVHN data. We try to improve the compositing algorithm used to build the IBSG dataset so that models trained with synthetic data perform as well as models trained with the original SVHN training …