Machine Learning Applications of Convolutional Neural Networks and Unet Architecture to Predict and Classify Demosponge Behavior

Machine Learning Applications of Convolutional Neural Networks and Unet Architecture to Predict and Classify Demosponge Behavior

Biological data sets are increasingly becoming information-dense, making it effective to use a computer science-based analysis. We used convolution neural networks (CNN) and the specific CNN architecture Unet to study sponge behavior over time. We analyzed a large time series of hourly high-resoluti...

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Bibliographic Details
Main Authors: Dominica Harrison, Fabio Cabrera De Leo, Warren J. Gallin, Farin Mir, Simone Marini, Sally P. Leys
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Water
Subjects:
convolutional neural networks (CNN)
unet
machine learning
semantic segmentation
demosponge behavior
classification
Online Access:https://www.mdpi.com/2073-4441/13/18/2512

Internet

https://www.mdpi.com/2073-4441/13/18/2512

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