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Undergraduate Research: Introducing Deep Learning-based Image Classification to Undergraduate Students

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Conference

2018 ASEE Annual Conference & Exposition

Location

Salt Lake City, Utah

Publication Date

June 23, 2018

Start Date

June 23, 2018

End Date

July 27, 2018

Conference Session

Computing Research

Tagged Division

Computing and Information Technology

Page Count

9

Permanent URL

https://peer.asee.org/31171

Download Count

24

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Paper Authors

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Deng Cao Central State University

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Dr. Deng Cao received his Ph.D in Computer Science from West Virginia University in 2013. He also earned two master degrees in Statistics and Physics from West Virginia University. Dr. Cao joined Central State University in 2013 and currently serves as an assistant professor in the department of Mathematics and Computer Science. His research interests include computer vision, machine learning and pattern recognition.
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Cadance Lowell Central State University

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Dr. Cadance Lowell is a Professor of Agriculture at Central State University and Chair of the Department of Agricultural Sciences. Her duties have included teaching botany, plant physiology, horticulture, fundamentals of biology, medicinal plants, sustainable agriculture, and serving as the Director of the campus greenhouse. She received a B.S. in Botany from Duke University, a M.S. in Botany from the University of Florida, Gainesville, and a Ph.D. in Horticulture from the University of Florida, Gainesville. Research was in the primary metabolism and carbon partitioning in grapefruit and transmission electron microscopy of the source-sink pathway. She did post-doctoral work with the USDA in Peoria, IL as a biochemist in soybean oligosaccharides before joining Central State University in 1989. Dr. Lowell maintains a research program in directed energy weed control. She mentors undergraduate students in funded research projects who have gone on to present at local, state and national conferences.

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Augustus Morris Central State University

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Dr. Augustus Morris is the Chair of the Manufacturing Engineering department at Central State University, Wilberforce, OH. He is also the Program Director of the NSF funded grant, Implementing Pathways for STEM Retention and Graduation (IPSRG). His research interests include robotic applications in agriculture, haptic devices, high altitude balloon payload design, and cellulose-based composite materials.

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Abstract

In the past few years, deep learning based methods has quickly become the state of the art in image classification and object detection. As one of the best deep learning structures, Convolutional Neural Network (CNN) is highly automated and requires little prior knowledge. Also, a customized CNN can be quickly built without a large database, if a pre-trained network is provided. These advantages make CNN suitable for undergraduate research. Funded by an 1890 Land Grant Research Project III, CNN is introduced to the undergraduate students in our institution and the students are trained to develop customized CNN in order to solve given image classification problems. The achieved goals and discovered issues are reported and discussed in this work. Overall, the results demonstrated a positive example of integrating modern technology and research into undergraduate classrooms.

Cao, D., & Lowell, C., & Morris, A. (2018, June), Undergraduate Research: Introducing Deep Learning-based Image Classification to Undergraduate Students Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. https://peer.asee.org/31171

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