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Deep Learning For Machine Vision

The purpose of the project is to evaluate the use of deep learning as an alternative to traditional machine vision inspection methods used in General Motors' assembly line.

The Tauber team will evaluate and test deep learning tools and algorithms and determine whether an opportunity for large-scale implementation exists. The insights developed will result in improved accuracy, as well as reduced downtime and cost.

View team project summary

Student Team:

Mabel Chan – EGL (BSE & MSE in Computer Science Engineering)

Konstantinos Chiotinis – Master of Business Administration

Soo Yeon (Sean) Lee – EGL (BSE & MSE in Computer Science Engineering)

Project Sponsors:

Amar Amad – Engineering Manager

William Keller – Sr. Manufacturing Project Engineer

Faculty Advisors:

Jeff Alden – College of Engineering

Sanjeev Kumar – Ross School of Business