Performance evaluation of RNX080 and RNY080 in CWE-Layer 1.

<p>Performance evaluation of RNX080 and RNY080 in CWE-Layer 1.</p>

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Bibliographic Details
Main Author:	Anwar Hossain Efat (19942283) (author)
Published:	2025
Subjects:	Medicine Cancer Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified require early detection precise areas responsible optimized regnet synergy optimal weight allocation offering valuable insights highlight critical regions ham1000 dataset demonstrates addressing challenges related model dominance dispersion layer ensemble approach enhance model interpretability skin lesion detection novel transfer learning div >< p layer weighted ensemble including various abnormalities cwe approach achieves 2 </ sup weighted ensemble >< sup model predictions skin lesions novel framework chi </ study fills practical applications impressive accuracy effective treatment current research boosts accuracy based framework art methods
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