Research output per year
Research output per year
Network
Recent external collaboration on country level. Dive into details by clicking on the dots or
Research output
-
Shape Classification Using Hydrodynamic Detection via a Sparse Large-Scale 2D-Sensitive Artificial Lateral Line
Wolf, B., Pirih, P., Kruusmaa, M. & van Netten, S., 9-Jan-2020, In : IEEE Access. 8, p. 11393-11404 12 p., 8954645.Research output: Contribution to journal › Article › Academic › peer-review
Open AccessFile -
Three-dimensional multi-source localization of underwater objects using convolutional neural networks for artificial lateral lines
Wolf, B. J., van de Wolfshaar, J. & van Netten, S. M., Jan-2020, In : Journal of the Royal Society Interface. 17, 162, 20190616.Research output: Contribution to journal › Article › Academic › peer-review
Open AccessFile -
Hydrodynamic Imaging using an all-optical 2D Artificial Lateral Line
Wolf, B. & van Netten, S., 6-May-2019, 2019 IEEE Sensors Applications Symposium (SAS). IEEE, p. 1-6Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
-
Recurrent neural networks for hydrodynamic imaging using a 2D-sensitive artificial lateral line
Wolf, B. J., Warmelink, S. & van Netten, S. M., 11-Jul-2019, In : Bioinspiration & biomimetics. 14, 5, 10 p., 055001.Research output: Contribution to journal › Article › Academic › peer-review
Open AccessFile -
Training submerged source detection for a 2D fluid flow sensor array with Extreme Learning Machines
Wolf, B. & van Netten, S., 15-Mar-2019, Eleventh International Conference on Machine Vision (ICMV 2018). SPIE.Digital Library, Vol. 11041. p. 1104126 8 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Open AccessFile
Datasets
-
2D-sensitive flow sensor array data set for five different objects
Wolf, B. (Creator) & van Netten, S. (Creator), University of Groningen, 2019
DOI: 10411/BWQMTQ
Dataset