Deleterious effects of uncertainty in color imagery streams on classification models

Syed Muslim Jameel, Manzoor Ahmed Hashmani, Hitham Al Hussain, Mobashar Rehman, Arif Budiman

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

2 Citations (Scopus)

Abstract

Image Classification (IC) is most prominent among other Artificial Intelligence (AI) domains. Mainly, IC participates rigorously for the development of society in a variety of application areas such as finance, marketing, health, industrial automation, education, and safety and security. Typically, an IC model takes image input data and tunes itself as per the required application task and classify accordingly. Among the various categories of images, color image category is better due to the capability of capturing more details, which are essential for classification purpose. However, the modern world demands Realtime or online image classification, which involves Imagery Streams. The highly likely uncertainty in Imagery Streams is due to non-stationary environment, for example, certain features or class boundaries which are valid at one-time step are not adequate for another time step. These uncertainties in Imagery Streams have deleterious effects on IC models, which causes performance degradation in terms of accuracy or make IC models, not in further use. Therefore, to overcome these issues, IC models need to adapt to changes caused by uncertainties in Imagery Streams. This paper focuses on the understanding the possible scenarios of such uncertainties in Color Imagery Streams, investigates the deleterious effects due to changes in Color Imagery Streams and provides the possible mitigation approach to overcome the issues in IC models. The contribution of this research is the first step towards an adaptive model development to mitigate the deleterious effects of uncertainty in Color Imagery Streams. This model will benefit many application areas and will directly contribute to the daily life of a society.

Original languageEnglish
Title of host publicationProceedings - 2019 1st International Conference on Artificial Intelligence and Data Sciences, AiDAS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7-11
Number of pages5
ISBN (Electronic)9781728130415
DOIs
Publication statusPublished - Sep 2019
Event1st International Conference on Artificial Intelligence and Data Sciences, AiDAS 2019 - Ipoh, Perak, Malaysia
Duration: 19 Sep 2019 → …

Publication series

NameProceedings - 2019 1st International Conference on Artificial Intelligence and Data Sciences, AiDAS 2019

Conference

Conference1st International Conference on Artificial Intelligence and Data Sciences, AiDAS 2019
Country/TerritoryMalaysia
CityIpoh, Perak
Period19/09/19 → …

Keywords

  • Color Imagery Stream Analytics
  • Machine Learning
  • Online Classification
  • Uncertainty in Classification

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