U-Net: A Versatile Deep Learning Architecture for Image

U-Net is an exceptional deep learning architecture that has gained immense popularity for its total game-changer performance in image segmentation tasks. Developed by Olaf Ronneberger, Philipp…

Deep Learning for Computer Vision: Models & Real World Applications

U-Net Image Segmentation in Keras - PyImageSearch

U-Net Explained: Understanding its Image Segmentation Architecture, by Conor O'Sullivan

The U-Net (actually) explained in 10 minutes

Introductory guide to Vision Transformers

Convolutional Neural Networks¶. Project: Dog Breed Classification¶, by Mr Sinha

Introduction to Deep Learning - GeeksforGeeks

U-Net Explained: Understanding its Image Segmentation Architecture, by Conor O'Sullivan

Semantic segmentation using an optical computer, by adh1s, Optalysys

Applied Sciences, Free Full-Text

Remote Sensing, Free Full-Text

Designing a High-Performance Deep Learning Theoretical Model for Biomedical Image Segmentation by Using Key Elements of the Latest U-Net-Based Architectures

Designing a High-Performance Deep Learning Theoretical Model for Biomedical Image Segmentation by Using Key Elements of the Latest U-Net-Based Architectures

FLUTE: A scalable federated learning simulation platform - Microsoft Research

PDF) U-Net and Its Variants for Medical Image Segmentation: A Review of Theory and Applications