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Engineering and Technology Journal
Article . 2021 . Peer-reviewed
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Engineering and Technology Journal
Article
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ZENODO
Article . 2021
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Object Detection System Using K-Means Clustering

Authors: S. Srihari; Prof. Sridhar Ranganathan;

Object Detection System Using K-Means Clustering

Abstract

Object Detection is one of the most popular applications in the branch of computer vision. While accuracy has always been the focus, focus has gradually also shifted to lightweight models. In this paper we propose a light weight system where object classification is not required but only object detection using clustering methods.

Keywords

Object detection , Computer vision, Elbow method, K - means clustering

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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