Explainable AI (XAI) driven skin cancer detection using transformer and CNN based architecture

Explainable AI (XAI) driven skin cancer detection using transformer and CNN based architecture

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.

Manylion Llyfryddiaeth
Prif Awduron:	Radiah, Faiza, Rahman, Kabasum, Asadullah, Lasania, Sohan, Md. Sohanur Rahman, Ahmed, Jaki
Awduron Eraill:	Alam, Md. Ashraful
Fformat:	Traethawd Ymchwil
Iaith:	English
Cyhoeddwyd:	Brac University 2024
Pynciau:	Skin cancer detection Disease detection CNN Deep learning Dermatoscopy VGG16 XAI Artificial intelligence > Medical applications Neural networks (Computer science) Deep learning (Machine learning)
Mynediad Ar-lein:	http://hdl.handle.net/10361/22837

Eitemau Tebyg

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Prostate cancer detection using deep learning neural network with transfer learning approach
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EAI4CC: deciphering lung and colon cancer categorization within a federated learning framework harnessing the power of explainable artificial intelligence
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PDFGuardian: An innovative approach to interpretable PDF malware detection using XAI with SHAP framework
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An interpretable diagnosis of retinal diseases using vision transformer and Grad-CAM
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Enhancing Monkeypox diagnosis: a machine learning approach for skin lession classification
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RetinalNet-500: a newly developed CNN model for eye disease detection
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