Automated Author Profile

Igor Eeckhaut

Laboratoire de Biologie des OrganismesMarins et Biomimétisme, University of Mons,PO Box 7000, Mons, Belgium

Current S-Index

101.7

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

0.5

Average Dataset Index per dataset

Total Datasets

223

Total datasets for this author

Average FAIR Score

77.4%

Average FAIR Score per dataset

Total Citations

0

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Projet CNDO - Sessions Underwater images collected by an Underwater Vision Census - 20210308_MDG-Toliara_UVC-01_01

Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation. These images can be annotated and shared to train IA models which can in turn predict the objects on the images. We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps..

Authors

  • Aina Le Don NOMENISOA ;
  • Yves Amoros MITONDRASOA ;
  • Gildas TODINANAHARY ;
  • Hubert Zafimampiravo EDWIN ;
  • Israel John Bunyan ;
  • Toky RAZAKARISOA ;
  • Tsiresimiary MANDIBILAZA ;
  • Michel RATSIZAFY ;
  • Saverio Raseta ;
  • Henitsoa Jaonalison ;
  • Jamal Mahafina ;
  • Igor Eeckhaut
0 Citations0 Mentions79% FAIR0.5 Dataset Index
10.5281/zenodo.153970502025

Projet CNDO - Sessions Underwater images collected by an Underwater Vision Census - 20210308_MDG-Toliara_UVC-01_01

Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation. These images can be annotated and shared to train IA models which can in turn predict the objects on the images. We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps..

Authors

  • Aina Le Don NOMENISOA ;
  • Yves Amoros MITONDRASOA ;
  • Gildas TODINANAHARY ;
  • Hubert Zafimampiravo EDWIN ;
  • Israel John Bunyan ;
  • Toky RAZAKARISOA ;
  • Tsiresimiary MANDIBILAZA ;
  • Michel RATSIZAFY ;
  • Saverio Raseta ;
  • Henitsoa Jaonalison ;
  • Jamal Mahafina ;
  • Igor Eeckhaut
0 Citations0 Mentions79% FAIR0.5 Dataset Index
10.5281/zenodo.153970962025

Projet CNDO - Sessions Underwater images collected by an Underwater Vision Census - 20210308_MDG-Toliara_UVC-01_01 - 20210308_MDG-Toliara_UVC-01_02

Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation. These images can be annotated and shared to train IA models which can in turn predict the objects on the images. We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps..

Authors

  • Aina Le Don NOMENISOA ;
  • Yves Amoros MITONDRASOA ;
  • Gildas TODINANAHARY ;
  • Hubert Zafimampiravo EDWIN ;
  • Israel John Bunyan ;
  • Toky RAZAKARISOA ;
  • Tsiresimiary MANDIBILAZA ;
  • Michel RATSIZAFY ;
  • Saverio Raseta ;
  • Henitsoa Jaonalison ;
  • Jamal Mahafina ;
  • Igor Eeckhaut
0 Citations0 Mentions79% FAIR0.4 Dataset Index
10.5281/zenodo.153971032025

Projet CNDO - Sessions Underwater images collected by an Underwater Vision Census - 20210308_MDG-Toliara_UVC-01_01 - 20210308_MDG-Toliara_UVC-01_02 - 20210309_MDG-Toliara_UVC-01_01

Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation. These images can be annotated and shared to train IA models which can in turn predict the objects on the images. We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps..

Authors

  • Aina Le Don NOMENISOA ;
  • Yves Amoros MITONDRASOA ;
  • Gildas TODINANAHARY ;
  • Hubert Zafimampiravo EDWIN ;
  • Israel John Bunyan ;
  • Toky RAZAKARISOA ;
  • Tsiresimiary MANDIBILAZA ;
  • Michel RATSIZAFY ;
  • Saverio Raseta ;
  • Henitsoa Jaonalison ;
  • Jamal Mahafina ;
  • Igor Eeckhaut
0 Citations0 Mentions79% FAIR0.5 Dataset Index
10.5281/zenodo.153971292025

Projet CNDO - Sessions Underwater images collected by an Underwater Vision Census - 20210308_MDG-Toliara_UVC-01_01 - 20210308_MDG-Toliara_UVC-01_02 - 20210309_MDG-Toliara_UVC-01_01 - 20210309_MDG-Toliara_UVC-01_02

Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation. These images can be annotated and shared to train IA models which can in turn predict the objects on the images. We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps..

Authors

  • Aina Le Don NOMENISOA ;
  • Yves Amoros MITONDRASOA ;
  • Gildas TODINANAHARY ;
  • Hubert Zafimampiravo EDWIN ;
  • Israel John Bunyan ;
  • Toky RAZAKARISOA ;
  • Tsiresimiary MANDIBILAZA ;
  • Michel RATSIZAFY ;
  • Saverio Raseta ;
  • Henitsoa Jaonalison ;
  • Jamal Mahafina ;
  • Igor Eeckhaut
0 Citations0 Mentions79% FAIR0.5 Dataset Index
10.5281/zenodo.153971512025

Projet CNDO - Sessions Underwater images collected by an Underwater Vision Census - 20210308_MDG-Toliara_UVC-01_01 - 20210308_MDG-Toliara_UVC-01_02 - 20210309_MDG-Toliara_UVC-01_01 - 20210309_MDG-Toliara_UVC-01_02 - 20210309_MDG-Toliara_UVC-01_03

Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation. These images can be annotated and shared to train IA models which can in turn predict the objects on the images. We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps..

Authors

  • Aina Le Don NOMENISOA ;
  • Yves Amoros MITONDRASOA ;
  • Gildas TODINANAHARY ;
  • Hubert Zafimampiravo EDWIN ;
  • Israel John Bunyan ;
  • Toky RAZAKARISOA ;
  • Tsiresimiary MANDIBILAZA ;
  • Michel RATSIZAFY ;
  • Saverio Raseta ;
  • Henitsoa Jaonalison ;
  • Jamal Mahafina ;
  • Igor Eeckhaut
0 Citations0 Mentions79% FAIR0.5 Dataset Index
10.5281/zenodo.153971672025

Projet CNDO - Sessions Underwater images collected by an Underwater Vision Census - 20210308_MDG-Toliara_UVC-01_01 - 20210308_MDG-Toliara_UVC-01_02 - 20210309_MDG-Toliara_UVC-01_01 - 20210309_MDG-Toliara_UVC-01_02 - 20210309_MDG-Toliara_UVC-01_03 - 20210310_MDG-Toliara_UVC-01_01

Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation. These images can be annotated and shared to train IA models which can in turn predict the objects on the images. We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps..

Authors

  • Aina Le Don NOMENISOA ;
  • Yves Amoros MITONDRASOA ;
  • Gildas TODINANAHARY ;
  • Hubert Zafimampiravo EDWIN ;
  • Israel John Bunyan ;
  • Toky RAZAKARISOA ;
  • Tsiresimiary MANDIBILAZA ;
  • Michel RATSIZAFY ;
  • Saverio Raseta ;
  • Henitsoa Jaonalison ;
  • Jamal Mahafina ;
  • Igor Eeckhaut
0 Citations0 Mentions79% FAIR0.5 Dataset Index
10.5281/zenodo.153971832025

Projet CNDO - Sessions Underwater images collected by an Underwater Vision Census - 20210308_MDG-Toliara_UVC-01_01 - 20210308_MDG-Toliara_UVC-01_02 - 20210309_MDG-Toliara_UVC-01_01 - 20210309_MDG-Toliara_UVC-01_02 - 20210309_MDG-Toliara_UVC-01_03 - 20210310_MDG-Toliara_UVC-01_01 - 20210310_MDG-Toliara_UVC-01_02

Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation. These images can be annotated and shared to train IA models which can in turn predict the objects on the images. We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps..

Authors

  • Aina Le Don NOMENISOA ;
  • Yves Amoros MITONDRASOA ;
  • Gildas TODINANAHARY ;
  • Hubert Zafimampiravo EDWIN ;
  • Israel John Bunyan ;
  • Toky RAZAKARISOA ;
  • Tsiresimiary MANDIBILAZA ;
  • Michel RATSIZAFY ;
  • Saverio Raseta ;
  • Henitsoa Jaonalison ;
  • Jamal Mahafina ;
  • Igor Eeckhaut
0 Citations0 Mentions79% FAIR0.5 Dataset Index
10.5281/zenodo.153971952025

Projet CNDO - Sessions Underwater images collected by an Underwater Vision Census - 20210308_MDG-Toliara_UVC-01_01 - 20210308_MDG-Toliara_UVC-01_02 - 20210309_MDG-Toliara_UVC-01_01 - 20210309_MDG-Toliara_UVC-01_02 - 20210309_MDG-Toliara_UVC-01_03 - 20210310_MDG-Toliara_UVC-01_01 - 20210310_MDG-Toliara_UVC-01_02 - 20210310_MDG-Toliara_UVC-01_03

Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation. These images can be annotated and shared to train IA models which can in turn predict the objects on the images. We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps..

Authors

  • Aina Le Don NOMENISOA ;
  • Yves Amoros MITONDRASOA ;
  • Gildas TODINANAHARY ;
  • Hubert Zafimampiravo EDWIN ;
  • Israel John Bunyan ;
  • Toky RAZAKARISOA ;
  • Tsiresimiary MANDIBILAZA ;
  • Michel RATSIZAFY ;
  • Saverio Raseta ;
  • Henitsoa Jaonalison ;
  • Jamal Mahafina ;
  • Igor Eeckhaut
0 Citations0 Mentions79% FAIR0.5 Dataset Index
10.5281/zenodo.153971992025

Projet CNDO - Sessions Underwater images collected by an Underwater Vision Census - 20210308_MDG-Toliara_UVC-01_01

Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation. These images can be annotated and shared to train IA models which can in turn predict the objects on the images. We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps..

Authors

  • Aina Le Don NOMENISOA ;
  • Yves Amoros MITONDRASOA ;
  • Gildas TODINANAHARY ;
  • Hubert Zafimampiravo EDWIN ;
  • Israel John Bunyan ;
  • Toky RAZAKARISOA ;
  • Tsiresimiary MANDIBILAZA ;
  • Michel RATSIZAFY ;
  • Saverio Raseta ;
  • Henitsoa Jaonalison ;
  • Jamal Mahafina ;
  • Igor Eeckhaut
0 Citations0 Mentions79% FAIR0.5 Dataset Index
10.5281/zenodo.153498142025