March 25, 2018
March 25, 2018
March 27, 2018
Community colleges provide a beneficial foundation for undergraduate education in STEM majors. To inspire community college students to pursue a major in STEM, it is crucial to adapt strategies that help facilitate this interest. With support from the Department of Education Minority Science and Engineering Improvement program (MSEIP) and the Hispanic-Serving Institution Science, Technology, Engineering and Mathematics (HIS STEM), an internship program with multiple colleges was developed between community colleges and a public four-year university to engage community college students in cutting-edge engineering research. In the summer of 2017, four community college students participated in a ten-week electrical and computer engineering research internship project at a four-year university research lab. The summer internship project aimed to develop a real-time handwritten digit recognition system leveraging Neural Networks and Nvidia’s Jetson Tx1 platform. Utilizing a modified Nvidia workflow, a robust digit recognition algorithm was designed using two industry standard programs for deep learning -- Tensor Flow and DIGITS. Nvidia’s live image recognition demonstration created the framework to interface a camera module that sends images to the input of the digit classifying network in real-time. The student interns designed experiments to test the robustness of the algorithm in their daily environment, from low light situations to cluttered backgrounds with the handwritten digit blending in. The internship project created a stimulating environment for student interns to gain research experiences and learn a wealth of knowledge in deep learning, real time pattern recognition systems and leading-edge hardware platforms. The experiences contained within the ten-week internship allowed the interns to drastically improve technical writing and presentations, experimental design, data analysis and management, teamwork, and perseverance. The ten-week research internship was an effective method for engaging aspiring community college students by teaching the tools and methodology for success within an engineering profession.
Mercurio, J. P., & Yamada, K., & Guzman, J. L., & Zhang, X., & Pong, W., & Enriquez, A. G., & Jiang, Z., & Chen, C., & Teh, K. S., & Mahmoodi, H., & Jiang, H., & Choi, A., & Iqbal, A. R. (2018, March), Inspiring Community College Students in Electrical and Computer Engineering Research through Live Digit Recognition using Nvidia’s Jetson Tx1 Paper presented at 2018 ASEE Zone IV Conference, Boulder, Colorado. https://peer.asee.org/29619
ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2018 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015