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Image Segmentation, UNet, and Deep Supervision Loss Using Keras Model
Sept. 28, 2022, 7:27 p.m. | shashank kumar
Towards Data Science - Medium towardsdatascience.com
Deep CNNs used for segmentation often suffer from vanishing gradients. Can we combat this by calculating loss at different output levels?
Image segmentation entails partitioning image pixels into different classes. Some applications include identifying tumour regions in medical images, separating land and water areas in drone images, etc. Unlike classification, where CNNs output a class probability score vector, segmentation requires CNNs to output an image.
Image segmentation of a tennis player (Source-Creative Commons Attribution 4.0 License) …convolutional-network deep learning image keras loss machine learning segmentation tensorflow unet
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