Performance metrics and number of parameters of the ResNet18 and the RCANet.

<p>Performance metrics and number of parameters of the ResNet18 and the RCANet.</p>

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Bibliographic Details
Main Author:	Mohammad Zolfaghari (20308480) (author)
Other Authors:	Hedieh Sajedi (18771134) (author)
Published:	2024
Subjects:	Plant Biology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified xlink "> aerobiology less human intervention achieved weighted f1 suggested attention block dorsal streams detect dorsal attention blocks cretan pollen dataset 69 %, 97 dorsal attention block dorsal ateetntion block ventral attention block pollen grains classification cpd ), pollen13k pollen grains basic block pollen grain automated classification 83 %, vdab ), tiny insects test step score values proposed method performed traditionally occipital lobe manual method fungal spores designed based channels related automated approach
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