Detection of microplastics using machine learning

Zenon Chaczko, Peter Wajs-Chaczko, David Tien, Yousef Haidar

Research output: Book chapter/Published conference paperConference paperpeer-review

4 Citations (Scopus)


Monitoring the presence of micro-plastics in human and animal habitats is fast becoming an important research theme due to a need to preserve healthy ecosystems. Microplastics pollute the environment and can represent a serious threat for biological organisms including the human body, as they can be inadvertently consumed through the food chain. To perceive and understand the level of microplastics pollution threats in the environment there is a need to design and develop reliable methodologies and tools that can detect and classify the different types of the microplastics. This paper presents results of our work related to exploration of methods and techniques useful for detecting suspicious objects in their respective ecosystem captured in hyperspectral images and then classifying these objects with the use of Neural Networks technique.
Original languageEnglish
Title of host publicationProceedings of 2019 International Conference on Machine Learning and Cybernetics, ICMLC 2019
PublisherIEEE Computer Society
Number of pages8
ISBN (Electronic)9781728128160
Publication statusPublished - 06 Jan 2020
Event18th International Conference on Machine Learning and
Cybernetics 2019: ICMLC 2019
- Kobe, Japan
Duration: 07 Jul 201910 Jul 2019 (conference info)

Publication series

NameProceedings - International Conference on Machine Learning and Cybernetics
ISSN (Print)2160-133X
ISSN (Electronic)2160-1348


Conference18th International Conference on Machine Learning and
Cybernetics 2019
Internet address


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