Areeba Masood Siddiqui1,2,*, Hyder Abbas3,4, Muhammad Asim5,6,*, Abdelhamied A. Ateya5, Hanaa A. Abdallah7
CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3135-3168, 2025, DOI:10.32604/cmes.2025.069926
- 30 September 2025
Abstract Timely and accurate diagnosis of skin diseases is crucial as conventional methods are time-consuming and prone to errors. Traditional trial-and-error approaches often aggregate multiple models without optimization by resulting in suboptimal performance. To address these challenges, we propose a novel Squid Game Optimization-Dimension Reduction-based Ensemble (SGO-DRE) method for the precise diagnosis of skin diseases. Our approach begins by selecting pre-trained models named MobileNetV1, DenseNet201, and Xception for robust feature extraction. These models are enhanced with dimension reduction blocks to improve efficiency. To tackle the aggregation problem of various models, we leverage the Squid Game Optimization… More >
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