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Transfer Learning Approach with Features Block Selection via Genetic Algorithm for High-Imbalance and Multi-Label Classification of HPA Confocal Microscopy Images.

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第一作者： Vincenzo,Taormina

第一单位： Dipartimento di Matematica e Informatica, Università degli Studi di Palermo, 90123 Palermo, Italy.

作者： Vincenzo,Taormina ^[1] ; Domenico,Tegolo ^[1] ; Cesare,Valenti ^[1]

作者单位： Dipartimento di Matematica e Informatica, Università degli Studi di Palermo, 90123 Palermo, Italy. ^[1]

关键词 binary relevance confocal microscope convolutional neural network fluorescence images genetic algorithm images label powerset multi-class multi-label classification support vector machine transfer learning

DOI 10.3390/bioengineering12121379

PMID 41463675

发布时间 2026-01-02

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Bioengineering (Basel, Switzerland)

2025年12卷12期

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Bioengineering (Basel, Switzerland)

2025年12卷12期

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Transfer Learning Approach with Features Block Selection via Genetic Algorithm for High-Imbalance and Multi-Label Classification of HPA Confocal Microscopy Images.

Bioengineering (Basel, Switzerland)

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Transfer Learning Approach with Features Block Selection via Genetic Algorithm for High-Imbalance and Multi-Label Classification of HPA Confocal Microscopy Images.

Bioengineering (Basel, Switzerland)

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Bioengineering (Basel, Switzerland)

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