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A Dataset of Laryngeal Endoscopic Images with Comparative Study on
  Convolution Neural Network Based Semantic Segmentation

A Dataset of Laryngeal Endoscopic Images with Comparative Study on Convolution Neural Network Based Semantic Segmentation

16 July 2018
M. Laves
J. Bicker
L. Kahrs
T. Ortmaier
ArXivPDFHTML

Papers citing "A Dataset of Laryngeal Endoscopic Images with Comparative Study on Convolution Neural Network Based Semantic Segmentation"

4 / 4 papers shown
Title
Reducing Annotation Burden: Exploiting Image Knowledge for Few-Shot Medical Video Object Segmentation via Spatiotemporal Consistency Relearning
Reducing Annotation Burden: Exploiting Image Knowledge for Few-Shot Medical Video Object Segmentation via Spatiotemporal Consistency Relearning
Zixuan Zheng
Yilei Shi
Chunlei Li
Jingliang Hu
Xiao Xiang Zhu
Lichao Mou
48
0
0
19 Mar 2025
Data Augmentation: a Combined Inductive-Deductive Approach featuring
  Answer Set Programming
Data Augmentation: a Combined Inductive-Deductive Approach featuring Answer Set Programming
Pierangela Bruno
Francesco Calimeri
Cinzia Marte
S. Perri
19
0
0
22 Oct 2023
ENet: A Deep Neural Network Architecture for Real-Time Semantic
  Segmentation
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
Adam Paszke
Abhishek Chaurasia
Sangpil Kim
Eugenio Culurciello
SSeg
235
2,059
0
07 Jun 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
287
9,156
0
06 Jun 2015
1