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
Implements the full U-Net architecture with skip connections for pixel-wise dense prediction across arbitrary imaging domains. Built on TensorFlow 1.x with demonstrated applications in radio astronomy (RFI mitigation), medical imaging, and synthetic pattern detection. Provides modular, domain-agnostic design allowing direct application to custom datasets without architecture modifications.
About unet
jakeret/unet
Generic U-Net Tensorflow 2 implementation for semantic segmentation
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