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Comparative analysis of machine learning algorithms for the..:
, In:
2023 IEEE International Workshop on Metrology for the Sea; Learning to Measure Sea Health Parameters (MetroSea)
,
Jalil, B.
;
Maggiani, L.
;
Valcarenghi, L.
- p. 116-120 , 2023
Link:
https://doi.org/10.1109/MetroSea58055.2023.10317314
RT T1 <cTitle>2023 IEEE International Workshop on Metrology for the Sea; Learning to Measure Sea Health Parameters (MetroSea)</cTitle>: T1 <Title>Comparative analysis of machine learning algorithms for the classification of underwater marine debris</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10317314&Exemplar=1&LAN=DE A1 Jalil, B. A1 Maggiani, L. A1 Valcarenghi, L. YR 2023 K1 Support vector machines K1 Performance evaluation K1 Machine learning algorithms K1 Artificial neural networks K1 Feature extraction K1 Boosting K1 Indexes K1 Marine debris K1 Underwater Pollution K1 Convolution Neural Networks K1 Random Forest K1 Neural Networks K1 Logistic Regression K1 Extreme Gradient Boosting SP 116 OP 120 LK http://dx.doi.org/https://doi.org/10.1109/MetroSea58055.2023.10317314 DO https://doi.org/10.1109/MetroSea58055.2023.10317314 SF ELIB - SuUB Bremen
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