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A CNN Framenwork Based on Line Annotations for Detecting Nematodes in
  Microscopic Images

A CNN Framenwork Based on Line Annotations for Detecting Nematodes in Microscopic Images

IEEE International Symposium on Biomedical Imaging (ISBI), 2020
21 April 2020
Long Chen
M. Strauch
M. Daub
X. Jiang
Marcus Jansen
Hans-Georg Luigs
Susanne Schultz-Kuhlmann
S. Krüssel
Dorit Merhof
ArXiv (abs)PDFHTML

Papers citing "A CNN Framenwork Based on Line Annotations for Detecting Nematodes in Microscopic Images"

4 / 4 papers shown
Quantifying Nematodes through Images: Datasets, Models, and Baselines of
  Deep Learning
Quantifying Nematodes through Images: Datasets, Models, and Baselines of Deep Learning
Zhipeng Yuan
Nasamu Musa
Katarzyna Dybal
Matthew Back
Daniel J. Leybourne
Po Yang
186
3
0
30 Apr 2024
High-throughput Phenotyping of Nematode Cysts
High-throughput Phenotyping of Nematode Cysts
Long Chen
M. Daub
Hans-Georg Luigs
Marcus Jansen
M. Strauch
Dorit Merhof
141
6
0
13 Oct 2021
I-Nema: A Biological Image Dataset for Nematode Recognition
I-Nema: A Biological Image Dataset for Nematode Recognition
Xuequan Lu
Yihao Wang
Sheldon Fung
Xue Qing
133
13
0
15 Mar 2021
NemaNet: A convolutional neural network model for identification of
  nematodes soybean crop in brazil
NemaNet: A convolutional neural network model for identification of nematodes soybean crop in brazil
A. Abade
L. Porto
P. Ferreira
Flávio de Barros Vidal
144
5
0
05 Mar 2021
1
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