Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales

Terms and Conditions

Twitter GitHub LinkedIn Bluesky Youtube

© 2026 ResearchTrend.AI, All rights reserved.

Home
Papers
2005.11368
Cited By

Gleason Grading of Histology Prostate Images through Semantic
Segmentation via Residual U-Net

Gleason Grading of Histology Prostate Images through Semantic Segmentation via Residual U-Net

22 May 2020

Amartya Kalapahar

Julio Silva-Rodríguez

Adrián Colomer

Fernando López-Mir

ArXiv (abs)PDF HTML

Papers citing "Gleason Grading of Histology Prostate Images through Semantic Segmentation via Residual U-Net"

5 / 5 papers shown

Self-supervised learning of a tailored Convolutional Auto Encoder for
histopathological prostate grading

Self-supervised learning of a tailored Convolutional Auto Encoder for histopathological prostate gradingEuropean Signal Processing Conference (EUSIPCO), 2023

Zahra Tabatabaei

Adrián Colomer

79

5

0

21 Mar 2023

Automated segmentation and morphological characterization of placental
histology images based on a single labeled image

Automated segmentation and morphological characterization of placental histology images based on a single labeled image

118

1

0

07 Oct 2022

A review of machine learning approaches, challenges and prospects for
computational tumor pathology

A review of machine learning approaches, challenges and prospects for computational tumor pathology

230

9

0

31 May 2022

Acoustic Echo Cancellation using Residual U-Nets

Acoustic Echo Cancellation using Residual U-Nets

J. Silva-Rodríguez

Adrián Castelló

183

3

0

20 Sep 2021

WeGleNet: A Weakly-Supervised Convolutional Neural Network for the
Semantic Segmentation of Gleason Grades in Prostate Histology Images

WeGleNet: A Weakly-Supervised Convolutional Neural Network for the Semantic Segmentation of Gleason Grades in Prostate Histology Images

Julio Silva-Rodríguez

Adrián Colomer

228

47

0

21 May 2021

Page 1 of 1