Chi2 weighted ensemble: A multi-layer ensemble approach for skin lesion classification using a novel framework - optimized RegNet synergy with Attention-Triplet

Anwar Hossain Efat

doi:10.1371/journal.pone.0321803

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Open Access

Peer-reviewed

Research Article

Chi² weighted ensemble: A multi-layer ensemble approach for skin lesion classification using a novel framework - optimized RegNet synergy with Attention-Triplet

Anwar Hossain Efat

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Validation, Visualization, Writing – original draft

* anwarhossainefat@gmail.com

Affiliation Department of Computer Science and Engineering, IUBAT - International University of Business Agriculture and Technology, Dhaka, Bangladesh

https://orcid.org/0009-0003-7999-1512

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Chi² weighted ensemble: A multi-layer ensemble approach for skin lesion classification using a novel framework - optimized RegNet synergy with Attention-Triplet

Anwar Hossain Efat

Published: May 20, 2025
https://doi.org/10.1371/journal.pone.0321803

About the Authors

Anwar Hossain Efat

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Validation, Visualization, Writing – original draft

* anwarhossainefat@gmail.com

Affiliation Department of Computer Science and Engineering, IUBAT - International University of Business Agriculture and Technology, Dhaka, Bangladesh

https://orcid.org/0009-0003-7999-1512

Competing Interests

The authors have declared that no competing interests exist.

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Olfactory receptor neurons
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Algorithms
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Lesions
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Skin tumors
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Ensemble methods
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Convolution
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Cutaneous melanoma
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Preprocessing
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