tf_unet and unet
These are successive versions of the same project, where the newer implementation (B) upgrades the original (A) from TensorFlow 1.x to TensorFlow 2.x while maintaining the same core U-Net architecture for image segmentation.
About tf_unet
jakeret/tf_unet
Generic U-Net Tensorflow implementation for image segmentation
This helps scientists and researchers automatically identify and outline specific features within images. You input an image containing objects of interest, and it outputs a segmented image highlighting those features. This is ideal for anyone working with various types of imaging data, from astronomy to medical research, who needs to precisely locate and measure objects or anomalies.
About unet
jakeret/unet
Generic U-Net Tensorflow 2 implementation for semantic segmentation
This tool helps scientists and researchers automatically outline or highlight specific objects within various types of images. You input an image containing objects you want to identify, and it outputs a segmented image where those objects are clearly delineated. This is ideal for those who work with medical scans, astronomical images, or any visual data requiring precise object isolation.
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