U-Net Image Segmentation with Convolutional Networks

Author(s): Buse Yaren Tekin

Originally published on Towards AI.

Step 1: Obtaining the dataset

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In our age, semantic segmentation on image data is frequently used for computer vision. U-Net is a backbone network that contains convolutional neural networks for masking objects.

U+1F9F6U-Net takes its name from its architecture similar to the letter U as seen in the figure. The input images are obtained as a segmented output map at the output.

You can access the basic level information and working architecture of the U-Net network in the article Image Segmentation with U-Net. This article describes the step-by-step coding of the U-Net in the Python programming… Read the full blog for free on Medium.

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Published via Towards AI