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D-LEMA: Deep Learning Ensembles from Multiple Annotations -- Application
  to Skin Lesion Segmentation

D-LEMA: Deep Learning Ensembles from Multiple Annotations -- Application to Skin Lesion Segmentation

14 December 2020
Z. Mirikharaji
Kumar Abhishek
S. Izadi
Ghassan Hamarneh
ArXivPDFHTML

Papers citing "D-LEMA: Deep Learning Ensembles from Multiple Annotations -- Application to Skin Lesion Segmentation"

5 / 5 papers shown
Title
HealNet -- Self-Supervised Acute Wound Heal-Stage Classification
HealNet -- Self-Supervised Acute Wound Heal-Stage Classification
Héctor Carrión
Mohammad Jafari
Hsin-ya Yang
Roslyn Rivkah
M. Rolandi
Marcella M. Gomez
Narges Norouzi
12
6
0
21 Jun 2022
A Survey on Deep Learning for Skin Lesion Segmentation
A Survey on Deep Learning for Skin Lesion Segmentation
Z. Mirikharaji
Kumar Abhishek
Alceu Bissoto
Catarina Barata
Sandra Avila
Eduardo Valle
M. Celebi
Ghassan Hamarneh
39
82
0
01 Jun 2022
A Novel Surrogate-assisted Evolutionary Algorithm Applied to
  Partition-based Ensemble Learning
A Novel Surrogate-assisted Evolutionary Algorithm Applied to Partition-based Ensemble Learning
A. Dushatskiy
Tanja Alderliesten
Peter A. N. Bosman
8
8
0
16 Apr 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
276
5,675
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,145
0
06 Jun 2015
1