A Hybrid Model for Early Melanoma Detection: Integrating YOLOv9 and Faster R-CNN for Enhanced Diagnostic Accuracy

A Hybrid Model for Early Melanoma Detection: Integrating YOLOv9 and Faster R-CNN for Enhanced Diagnostic Accuracy

Melanoma accounts for only 1% of skin cancer diagnoses yet causes the majority of skin cancer-related deaths due to its rapid progression and high metastatic potential. Early and accurate detection is crucial for improving patient outcomes; however, existing deep learning models often struggle to ba...

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Bibliographic Details
Main Authors: Mohamed I. Marie, Mohamed S. Elredeny, Ahmad Essayed Yakoub
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Melanoma detection
hybrid architecture
YOLOv9
faster R-CNN
deep learning
computer vision
Online Access:https://ieeexplore.ieee.org/document/11077147/
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https://ieeexplore.ieee.org/document/11077147/

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