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…

FID-Net: A versatile deep neural network architecture for NMR spectral reconstruction and virtual decoupling - UCL Discovery

Accurate and Versatile 3D Segmentation of Plant Tissues at Cellular Resolution

The Reproduction of “Image-to-Image Translation with Conditional Adversarial Networks”, by Damian Voorhout

Deep Learning Attention Mechanism in Medical Image Analysis: Basics and Beyonds-Scilight

Deep Q-Learning - GeeksforGeeks

Image segmentation using UNET. It is the process of partitioning an…, by Hemraj Choudhary

Neuromation Partner Insilico closed a strategic round of funding, by Neuromation, Neuromation

Image Segmentation with U-Net - Analytics Vidhya

Understanding the Architecture of the .NET Framework: An Overview

Self-Supervised Scene De-occlusion, by Jae Duk Seo

Guided-pix2pix 簡介 — Guided Image-to-Image Translation with Bi-Directional Feature Transformation, by xiao sean

U-Net: A Versatile Deep Learning Architecture for Image Segmentation, by Alexquesada

Introduction to Deep Learning - GeeksforGeeks