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A Skin Cancer Classfication System built using Deep Convolutional Neural Networks in conjunction with a hair removal and segmentation pre-processing pipeline.

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Name		Name	Last commit message	Last commit date
Latest commit History 2 Commits
assets		assets
7-Class_FinalX.h5		7-Class_FinalX.h5
Classifier.ipynb		Classifier.ipynb
README.md		README.md
img_processing.py		img_processing.py
imquantize.py		imquantize.py
process_single.py		process_single.py
segmentation.py		segmentation.py
single.py		single.py
thresholding.py		thresholding.py

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Skin Cancer Classification using Deep Convolutional Neural Networks with Hair Removal Pre-processing Pipeline

About the System

A Skin Cancer Classfication System built using Deep Convolutional Neural Networks in conjunction with a hair removal and segmentation pre-processing pipeline.

Black Hat and Top Hat algorithms are used to remove black and white hairs from images respectively
Saliency segmentation is used to isolate the region of interest in skin cancer images
Segmented images are used to train the Deep Convolutional Neural Network

Pre-processing Pipeline Stage 1

Pre-processing Pipeline Stage 2

Architecture of Deep Convolutional Neural Network

About

A Skin Cancer Classfication System built using Deep Convolutional Neural Networks in conjunction with a hair removal and segmentation pre-processing pipeline.

opencv deep-learning tensorflow numpy scikit-learn image-processing tophat blackhat convolutional-neural-networks

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