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Medical Melanoma Detection - TensorFlow U-Net Tutorial

Offered By: Eran Feit via YouTube

Tags

TensorFlow Courses Deep Learning Courses Computer Vision Courses Neural Networks Courses Keras Courses Image Segmentation Courses Medical Imaging Courses Data Augmentation Courses U-Net Courses

Course Description

Overview

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Learn to implement and train a U-Net model for melanoma detection using TensorFlow and Keras in this comprehensive tutorial. Begin with data preparation, accessing and preprocessing a substantial dataset of melanoma images and corresponding masks. Explore data augmentation techniques to improve model results. Build a U-Net model using TensorFlow and Keras, then guide through the training process to optimize melanoma detection. Test the pre-trained model on fresh images, generating masks that highlight melanoma regions. Visualize results in real-time, comparing predicted masks with ground truth. Covers U-Net architecture, dataset preparation, model building, training, testing, and result visualization in a step-by-step approach.

Syllabus

Intro !!!!!!!
The U-net architecture
Download the dataset and prepare the data
Build The U-net model
Train the model
Test the model with new fresh images


Taught by

Eran Feit

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