A Hybrid Learnable Fusion of ConvNeXt and Swin Transformer for Optimized Image Classification

Medical image classification often relies on CNNs to capture local details (e.g., lesions, nodules) or on transformers to model long-range dependencies. However, each paradigm alone is limited in addressing both fine-grained structures and broader anatomical context. We propose ConvTransGFusion, a h...

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Bibliographic Details
Main Authors: Jaber Qezelbash-Chamak, Karen Hicklin
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:IoT
Subjects:
Online Access:https://www.mdpi.com/2624-831X/6/2/30
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