A deep learning approach to detect and identify live freshwater macroinvertebrates
Author:
Funder
Région Bretagne
Publisher
Springer Science and Business Media LLC
Subject
Aquatic Science,Ecology, Evolution, Behavior and Systematics
Link
https://link.springer.com/content/pdf/10.1007/s10452-023-10053-7.pdf
Reference71 articles.
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3. Birk S, Bonne W, Borja A et al (2012) Three hundred ways to assess Europe’s surface waters: an almost complete overview of biological methods to implement the water framework directive. Ecol Ind 18:31–41
4. Bjerge K, Nielsen JB, Sepstrup MV et al (2021) An automated light trap to monitor moths (lepidoptera) using computer vision-based tracking and deep learning. Sensors 21(2):343
5. Bonneau M, Vayssade JA, Troupe W et al (2020) Outdoor animal tracking combining neural network and time-lapse cameras. Comput Electron Agric 168(105):150
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1. Automated identification of aquatic insects: A case study using deep learning and computer vision techniques;Science of The Total Environment;2024-07
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