Skin disease detection and classification using deep learning

Skin disease detection and classification using deep learning

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.

Bibliografiske detaljer
Main Authors:	Shuvon, Mehedi Hasan, Sadia, Rowshanara, Shormi, Shanjida Habib, Arafin, Umma Tania, Chowdhury, Md. Rawha Mikdad
Andre forfattere:	Rhaman, Md. Khalilur
Format:	Thesis
Sprog:	English
Udgivet:	Brac University 2022
Fag:	Image processing Deep learning MobileNetV2 InceptionV3 ResNetV2 Epoch Softmax Skin disease KNN CNN Detection Tensorflow Keras Layer Dense layer Machine learning Image processing > Digital techniques. Cognitive learning theory (Deep learning)
Online adgang:	http://hdl.handle.net/10361/17027

Lignende værker

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Detection of coronary artery blockage at an early stage using effective deep learning technique
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Deep neural network models for COVID-19 diagnosis from CT-Scan, explainability and analysis using trained models
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Gender classification in Bangla language using deep learning-based voice analysis
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A descriptive study on development of a transfer learning based fault detection model using 2D CNN for air compressors
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Masked face identification using face recognition
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A deep learning approach towards soft biometrics attributes prediction using CNN
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Anomalous behavior detection using Spatio temporal Feature and 3D CNN model for Surveillance
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A comparison of deep learning U‐Net architectures for semantic segmentation on panoramic X-ray images
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An efficient deep learning approach to detect skin Cancer
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