This repository contains a deep learning-based medical image segmentation system developed at the Budapest University of Technology and Economics. The system utilizes an encoder-decoder architecture, ...

In this proposed study, SegNet is used for segmentation of cellular structures in high-resolution histopathological images. SegNet is a deep convolutional encoder-decoder architecture used for ...

(* U-Net architecture is a deep learning image segmentation architecture introduced by Olaf Ronneberger, Philipp Fischer, and Thomas Brox in 2015. Its U shape design consists of two parts. The left ...

Keywords: deep learning, U-net, medical image segmentation, pulmonarty embolism, CNN -convolutional neural network. Citation: Zhan S, Yuan Q, Lei X, Huang R, Guo L, Liu K and Chen R (2024) BFNet: a ...

The AttendSeg deep learning model performs semantic segmentation at an accuracy that is almost on-par with RefineNet while cutting down the number of parameters to 1.19 million.