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Object Detection Techniques: Overview and Performance Comparison

  • University of Strathclyde

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

16 Scopus citations

Abstract

Object detection algorithms are improving by the minute. There are many common libraries or application program interfaces (APIs) to use. The most two common ones are Microsoft Azure Cloud object detection and Google Tensorflow object detection. The first is an online-network based API, while the second is an offline machine-based API. Both have their advantages and disadvantages. A direct comparison between the most common object detection methods helps in finding the best solution for advance system integration. This paper will discuss both methods and compare them in terms of accuracy, complexity and practicality. It will show advantages and also limitations of each method, and possibilities for improvement.

Original languageEnglish
Title of host publication2019 IEEE 19th International Symposium on Signal Processing and Information Technology, ISSPIT 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728153414
DOIs
StatePublished - Dec 2019
Event19th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2019 - Ajman, United Arab Emirates
Duration: 10 Dec 201912 Dec 2019

Publication series

Name2019 IEEE 19th International Symposium on Signal Processing and Information Technology, ISSPIT 2019

Conference

Conference19th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2019
Country/TerritoryUnited Arab Emirates
CityAjman
Period10/12/1912/12/19

Keywords

  • Azure Cloud
  • Object detection
  • Tensorflow

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