scholarly article | Q13442814 |
P2093 | author name string | Sietse M van Netten | |
Ben J Wolf | |||
Jos van de Wolfshaar | |||
P2860 | cites work | Imaging dipole flow sources using an artificial lateral-line system made of biomimetic hair flow sensors | Q30437111 |
Artificial fish skin of self-powered micro-electromechanical systems hair cells for sensing hydrodynamic flow phenomena. | Q36187787 | ||
Hydrodynamic detection by cupulae in a lateral line canal: functional relations between physics and physiology | Q36325700 | ||
Representation learning: a review and new perspectives | Q38115908 | ||
A fish perspective: detecting flow features while moving using an artificial lateral line in steady and unsteady flow | Q42007936 | ||
Performance of neural networks for localizing moving objects with an artificial lateral line. | Q47766518 | ||
Nonlinear estimation-based dipole source localization for artificial lateral line systems. | Q51238977 | ||
Artificial lateral line with biomimetic neuromasts to emulate fish sensing. | Q51758006 | ||
Source location encoding in the fish lateral line canal. | Q51944897 | ||
Velocity- and acceleration-sensitive units in the trunk lateral line of the trout | Q67999077 | ||
The functioning and significance of the lateral-line organs | Q76481938 | ||
Estimating position and velocity of a submerged moving object by the clawed frog Xenopus and by fish--a cybernetic approach | Q81318286 | ||
Recurrent neural networks for hydrodynamic imaging using a 2D-sensitive artificial lateral line | Q93024200 | ||
P433 | issue | 162 | |
P921 | main subject | convolutional neural network | Q17084460 |
P304 | page(s) | 20190616 | |
P577 | publication date | 2020-01-22 | |
P1433 | published in | Journal of the Royal Society Interface | Q2492390 |
P1476 | title | Three-dimensional multi-source localization of underwater objects using convolutional neural networks for artificial lateral lines | |
P478 | volume | 17 |
Q90395830 | Optimal Flow Sensing for Schooling Swimmers | cites work | P2860 |
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