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Detect-and-Segment: a Deep Learning Approach to Automate Wound Image
  Segmentation

Detect-and-Segment: a Deep Learning Approach to Automate Wound Image Segmentation

2 November 2021
G. Scebba
Jia Zhang
Sabrina Catanzaro
C. Mihai
O. Distler
M. Berli
W. Karlen
ArXivPDFHTML

Papers citing "Detect-and-Segment: a Deep Learning Approach to Automate Wound Image Segmentation"

4 / 4 papers shown
Title
Multi-modal wound classification using wound image and location by Xception and Gaussian Mixture Recurrent Neural Network (GMRNN)
Multi-modal wound classification using wound image and location by Xception and Gaussian Mixture Recurrent Neural Network (GMRNN)
Ramin Mousa
Ehsan Matbooe
Hakimeh Khojasteh
Amirali Bengari
Mohammadmahdi Vahediahmar
24
1
0
12 May 2025
Advancing Wound Filling Extraction on 3D Faces: Auto-Segmentation and
  Wound Face Regeneration Approach
Advancing Wound Filling Extraction on 3D Faces: Auto-Segmentation and Wound Face Regeneration Approach
Duong Q. Nguyen
Thinh D. Le
P. D. Nguyen
Nga T.K. Le
H. Nguyen-Xuan
24
4
0
04 Jul 2023
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision
  Applications
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew G. Howard
Menglong Zhu
Bo Chen
Dmitry Kalenichenko
Weijun Wang
Tobias Weyand
M. Andreetto
Hartwig Adam
3DH
948
20,549
0
17 Apr 2017
A Survey on Deep Learning in Medical Image Analysis
A Survey on Deep Learning in Medical Image Analysis
G. Litjens
Thijs Kooi
B. Bejnordi
A. Setio
F. Ciompi
Mohsen Ghafoorian
Jeroen van der Laak
Bram van Ginneken
C. I. Sánchez
OOD
278
10,608
0
19 Feb 2017
1