Performance of constituent models.

<p>Performance of each individual model used to create the ensemble models (n = 3). In compliance with standard practice, all models from the cross-validation experiments are discarded. To measure the performance of the methods, i.e., those starting with M- represents Mask R-CNN and U- for U-N...

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Bibliographic Details
Main Author:	Arjay Cayetano (20150181) (author)
Other Authors:	Christoph Stransky (14050964) (author), Andreas Birk (20284906) (author), Thomas Brey (438722) (author)
Published:	2024
Subjects:	Genetics Biotechnology Cancer Science Policy Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified routine stock assessment fish population dynamics different advanced concepts attain satisfactory accuracy minimize human bias interactive website housing based approaches based new explainable ai interactive ai based methods human experts many ai ai training ai ). transfer learning traditionally obtained recently published platform presented modern methods mask r machine learning important aspect ensemble learning early implementations driven platform directly involved direct compatibility designed utilizing continual learning concerns regarding artificial intelligence age estimates additional use
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Performance of constituent models.

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