Object Detection for E-Commerce: A Survey |
Author(s): |
| Suraj Khanna , MET�s Bhujbal Knowledge City, Institute of Engineering; Aditya Jaiswal, MET�s Bhujbal Knowledge City, Institute of Engineering; Ravi Kothari, MET�s Bhujbal Knowledge City, Institute of Engineering; Piyush Patil, MET�s Bhujbal Knowledge City, Institute of Engineering |
Keywords: |
| Object Detection for E-Commerce, Python Web Scraping, Image Recognition, Image Classification, YOLO Algorithm, OpenCV, Python Qt Designer, TensorFlow, Deep Learning, Convolutional Neural Network (CNN) |
Abstract |
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Object Detection for E-Commerce will merely focus on objects that are available to buy from the E-Commerce websites. Object Detection for E-Commerce will be an interface-based application which will accept a user uploaded video and will scan the whole video thoroughly for the objects that are available to buy from the market. As soon as the object gets detected, the user can get the relevant links from the E-Commerce websites to buy that object. This interface, in simple words, will do the work of finding that object or the item over the E-Commerce market. The project will be based on Machine Learning and will be created in Python programming language. For Image Detection and classification, which is the core part of the project, different Image recognition and classification algorithms will be used. Thus, for helping the users in shopping and providing them with a touch-to-shop experience this interface application would be very beneficial. |
Other Details |
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Paper ID: IJSRDV7I120366 Published in: Volume : 7, Issue : 12 Publication Date: 01/03/2020 Page(s): 334-336 |
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