Event Title

Marking artifacts in images using machine learning

Advisor(s)

Dr. Chihway Chang, University of Chicago

Location

Room A119

Start Date

26-4-2019 10:05 AM

End Date

26-4-2019 10:20 AM

Abstract

With the utilization of machine learning, computers have been able to efficiently classify data. Deep learning, a division of machine learning, uses multiple nonlinear processing units. Convolutional neural networks are a machine learning model patterned after the structure of an animal’s visual cortex. In our project, deep learning and convolutional neural networks were both used to distinguish cosmic rays, artifacts characterized by high-energy radiation, in images taken by the National Optical Astronomy Observatory’s telescopes. Once we had constructed a deep convolutional neural network, this network was trained and fine-tuned continuously until its classifications reached maximum accuracy.

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Apr 26th, 10:05 AM Apr 26th, 10:20 AM

Marking artifacts in images using machine learning

Room A119

With the utilization of machine learning, computers have been able to efficiently classify data. Deep learning, a division of machine learning, uses multiple nonlinear processing units. Convolutional neural networks are a machine learning model patterned after the structure of an animal’s visual cortex. In our project, deep learning and convolutional neural networks were both used to distinguish cosmic rays, artifacts characterized by high-energy radiation, in images taken by the National Optical Astronomy Observatory’s telescopes. Once we had constructed a deep convolutional neural network, this network was trained and fine-tuned continuously until its classifications reached maximum accuracy.