Overview
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Learn to implement and train a Res-UNet model for Melanoma detection using TensorFlow and Keras in this comprehensive tutorial. Explore the Res-UNet architecture, construct the model using TensorFlow and Keras, and guide through the training process to optimize melanoma identification from skin lesion images. Test the pre-trained model on fresh images, generate masks highlighting potential melanoma regions, and visualize results by comparing predicted masks with ground truth. Gain hands-on experience in building, training, and evaluating a deep learning model for medical image segmentation, with practical insights into TensorFlow implementation and real-time result visualization.
Syllabus
Intro !!!!!!!
The Res-U-net architecture
Build The Res-U-net model
Train the model
Test the model with new fresh images
Taught by
Eran Feit