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A hybrid architecture with separable convolutions and attention for lung and colon cancer detection

Early and accurate detection of lung and colon cancer is critical for improving patient survival rates. However, conventional classification techniques often struggle with the complexity of medical imaging data. In this study, we propose a novel hybrid architecture, the Separable Convolution and Att...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Md. Darun Nayeem, Md. Emdadul Hasan Shishir, Munshi Touibur Rahman, Zeeshan Chowdhury Juwel, Sagor Sutradhar, Sudipto Chaki, Md. Saifur Rahman, A.B.M. Shawkat Ali
Format: Artigo
Sprache:Inglês
Veröffentlicht: Elsevier 2025-12-01
Schriftenreihe:Array
Schlagworte:
Deep learning
Separable convolutions
Residual connections
Attention mechanisms
Lung cancer classification
Colon cancer detection
Online-Zugang:http://www.sciencedirect.com/science/article/pii/S2590005625002188
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