1. Digital Library Home
  2. Theses & Project Reports
  3. B.Tech. Project Reports
Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/9962
Full metadata record
DC FieldValueLanguage
dc.contributor.authorEkaghara, Mayank-
dc.contributor.authorTomar, Aditya-
dc.contributor.authorBharti, Monika [Guided by]-
dc.date.accessioned2023-09-13T04:16:30Z-
dc.date.available2023-09-13T04:16:30Z-
dc.date.issued2023-
dc.identifier.urihttp://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/9962-
dc.descriptionEnrollment No. 191406, 191431en_US
dc.description.abstractjuitOLX is an e-commerce website designed to provide students with a sustainable and cost-effective way to buy and sell items they need. To promote sustainability and legal compliance, the website has incorporated a machine learning (ML) model using the YOLOv3 algorithm. This model detects illegal objects in images uploaded by students before they are listed on the website. juitOLX is built using the MERN stack, which includes MongoDB, ExpressJS, ReactJS, and NodeJS, providing a robust and scalable platform with real-time updates for buyers and sellers. The website offers features such as image uploads, search functionality, messaging system, and a seamless and transparent buying and selling experience. By promoting sustainability, responsible consumption, and legal compliance, juitOLX has the potential to revolutionize e-commerce platforms for students.en_US
dc.language.isoen_USen_US
dc.publisherJaypee University of Information Technology, Solan, H.P.en_US
dc.subjectYOLOen_US
dc.subjectOLXen_US
dc.subjecte-commerceen_US
dc.subjectMachine learningen_US
dc.titleJUIT-OLXen_US
dc.typeProject Reporten_US
Appears in Collections:B.Tech. Project Reports

Files in This Item:
File Description SizeFormat 
JUIT-OLX.pdf6.59 MBAdobe PDFView/Open
Show simple item record


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.