Cowpea sorter: An alternative to the manual cowpea sorting process

dc.contributor.authorSalley, Kawusara Nurudeen
dc.date.accessioned2020-05-11T11:54:03Z
dc.date.available2020-05-11T11:54:03Z
dc.date.issued2019
dc.descriptionCapstone Project submitted to the Department of Engineering, Ashesi University in partial fulfillment of the requirements for the award of Bachelor of Science degree in Electrical and Electronic Engineering, April 2019en_US
dc.description.abstractCowpea traders find the manual sorting process of cowpeas laborious and time-consuming. Based on the volume of cowpeas and the proportion of damaged cowpeas, the process can span a time interval of about 6 hours. This project integrates the power of computer vision and convolutional neural networks to develop a solution for the cowpea trader to effectively segregate good cowpeas from the damaged ones.en_US
dc.description.sponsorshipAshesi Universityen_US
dc.identifier.urihttp://hdl.handle.net/20.500.11988/543
dc.language.isoen_USen_US
dc.subjectagricultural productsen_US
dc.subjectcowpea retaileren_US
dc.subjectVigna unguiculataen_US
dc.subjectquality evaluationen_US
dc.subjectcomputer visionen_US
dc.subjectConvolutional Neural Network (CNN)en_US
dc.titleCowpea sorter: An alternative to the manual cowpea sorting processen_US
dc.typeCapstone projecten_US

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