METAHEURISTIC-AI ENHANCED CUSTOM DEEP LEARNING NETWORK OPTIMIZED WITH SAND CAT SWARM ALGORITHM FOR ORAL CANCER DIAGNOSIS

Oral cancer remains a major global health concern due to its high mortality rates. To address this, a novel hybrid deep learning framework is proposed that combines a Convolutional Neural Network (CNN) with Sand Cat Swarm Optimization (SCSO) for the effective classification of oral squamous cell car...

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Bibliografiska uppgifter

Huvudupphov:	Vinod Kumar Venkatesan, V Sujatha, Audithan Sivaraman, S Durga Devi, Praveen SR Konduri
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	XLESCIENCE 2025-06-01
Serie:	International Journal of Advances in Signal and Image Sciences
Ämnen:	oral cancer classification, convolutional neural network, sand cat swarm optimization, histopathological images, hyperparameter tuning, deep learning, metaheuristic optimization.
Länkar:	https://xlescience.org/index.php/IJASIS/article/view/280
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