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Aquatic Toxic Analysis by Monitoring Fish Behavior Using Computer Vision: A Recent Progress
Joint Authors
Xia, Chunlei
Fu, Longwen
Liu, Zuoyi
Liu, Hui
Liu, Yuedan
Chen, L.
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-04-03
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Video tracking based biological early warning system achieved a great progress with advanced computer vision and machine learning methods.
Ability of video tracking of multiple biological organisms has been largely improved in recent years.
Video based behavioral monitoring has become a common tool for acquiring quantified behavioral data for aquatic risk assessment.
Investigation of behavioral responses under chemical and environmental stress has been boosted by rapidly developed machine learning and artificial intelligence.
In this paper, we introduce the fundamental of video tracking and present the pioneer works in precise tracking of a group of individuals in 2D and 3D space.
Technical and practical issues suffered in video tracking are explained.
Subsequently, the toxic analysis based on fish behavioral data is summarized.
Frequently used computational methods and machine learning are explained with their applications in aquatic toxicity detection and abnormal pattern analysis.
Finally, advantages of recent developed deep learning approach in toxic prediction are presented.
American Psychological Association (APA)
Xia, Chunlei& Fu, Longwen& Liu, Zuoyi& Liu, Hui& Chen, L.& Liu, Yuedan. 2018. Aquatic Toxic Analysis by Monitoring Fish Behavior Using Computer Vision: A Recent Progress. Journal of Toxicology،Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1202725
Modern Language Association (MLA)
Xia, Chunlei…[et al.]. Aquatic Toxic Analysis by Monitoring Fish Behavior Using Computer Vision: A Recent Progress. Journal of Toxicology No. 2018 (2018), pp.1-11.
https://search.emarefa.net/detail/BIM-1202725
American Medical Association (AMA)
Xia, Chunlei& Fu, Longwen& Liu, Zuoyi& Liu, Hui& Chen, L.& Liu, Yuedan. Aquatic Toxic Analysis by Monitoring Fish Behavior Using Computer Vision: A Recent Progress. Journal of Toxicology. 2018. Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1202725
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1202725