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Little Caesars Pizza Quality Evaluator

dc.contributor.authorAkcay, Batuhan
dc.contributor.authorAlptekin, Susie
dc.contributor.authorJi, Ziyang
dc.contributor.authorLi, Kevin
dc.contributor.authorYao, Yue
dc.contributor.authorYoo, Ran
dc.date.accessioned2021-04-29T19:12:12Z
dc.date.available2021-04-29T19:12:12Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/2027.42/167246
dc.identifier.urihttps://youtu.be/Kp-QOyMni_I
dc.description.abstractLittle Caesar Enterprises Inc. is the third-largest pizza chain in the United States. It operates and franchises pizza restaurants internationally. Little Caesars strives to always deliver the best pizzas to its customer. However, it is not easy to maintain consistency in quality at every place and every time. One way to tackle this problem is to establish an automated pizza quality checking process. Our team uses Image Analysis and Computer Vision to help Little Caesars accomplish this goal. In the past year, we created a system that performs quality checking after pizzas come out of the oven and detects bad quality pizzas before being served to customers. The system is also connected to an online web application that offers real-time specific feedback to Little Caesars employees regarding the pizza quality. Employees are able to make changes as per the advice.
dc.subjectMachine Learning
dc.subjectComputer Vision
dc.subjectLittle Caesars
dc.titleLittle Caesars Pizza Quality Evaluator
dc.typeTechnical Report
dc.subject.hlbtoplevelEngineering
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/167246/1/Honors_Final_Report-Ziyang_Ji.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/167246/2/Honors_Capstone_Slides-Ziyang_Ji.pptx
dc.identifier.doihttps://dx.doi.org/10.7302/921
dc.working.doi10.7302/921en
dc.owningcollnameHonors Program, The College of Engineering


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