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Object Detection of Furniture and Home Goods Using Advanced Computer Vision | IEEE Conference Publication | IEEE Xplore

Object Detection of Furniture and Home Goods Using Advanced Computer Vision


Abstract:

Object Detection Technology has been a subject to much research and development due to increasing use of images and videos as data sources and their huge number of applic...Show More

Abstract:

Object Detection Technology has been a subject to much research and development due to increasing use of images and videos as data sources and their huge number of applications. Traditional models for object detection had limitations in training and did not use transfer learning for their benefit. With the evolution of deep learning and Neural networks, newer and powerful tools have made way to achieve Object Detection in real-time, with the added advantage of transfer learning and detection of multiple instances of different classes of interest in the given image context. The proposed system is an Object Detection model based on the Single Shot Detector (SSD) algorithm trained with MobileNetV2 feature extraction that can be utilized and integrated in e-commerce, hospitality industry, security and surveillance, real estate, self-driving cars and floor inventory management.
Date of Conference: 24-26 February 2022
Date Added to IEEE Xplore: 16 June 2022
ISBN Information:
Conference Location: Kolkata, India

I. Introduction

As a technology, Computer Vision has diverse subfields. Image Classification[15] is an area of computer science that studies how computer algorithms classify or assign class to real-world object instances in images and videos. Another area is Object Detection, which is associated with the process of locating and identifying object instances of specific classes in a given image that contains instances from several classes. An image bound with boxes around the detected object and the name of the object is the output of an object detection algorithm.

References

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