Three-dimensional multi-source localization of underwater objects using convolutional neural networks for artificial lateral lines

scientific article published on 22 January 2020

Three-dimensional multi-source localization of underwater objects using convolutional neural networks for artificial lateral lines is …
instance of (P31):
scholarly articleQ13442814

External links are
P356DOI10.1098/RSIF.2019.0616
P932PMC publication ID7014811
P698PubMed publication ID31964270

P2093author name stringSietse M van Netten
Ben J Wolf
Jos van de Wolfshaar
P2860cites workImaging dipole flow sources using an artificial lateral-line system made of biomimetic hair flow sensorsQ30437111
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 physiologyQ36325700
Representation learning: a review and new perspectivesQ38115908
A fish perspective: detecting flow features while moving using an artificial lateral line in steady and unsteady flowQ42007936
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 troutQ67999077
The functioning and significance of the lateral-line organsQ76481938
Estimating position and velocity of a submerged moving object by the clawed frog Xenopus and by fish--a cybernetic approachQ81318286
Recurrent neural networks for hydrodynamic imaging using a 2D-sensitive artificial lateral lineQ93024200
P433issue162
P921main subjectconvolutional neural networkQ17084460
P304page(s)20190616
P577publication date2020-01-22
P1433published inJournal of the Royal Society InterfaceQ2492390
P1476titleThree-dimensional multi-source localization of underwater objects using convolutional neural networks for artificial lateral lines
P478volume17

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Q90395830Optimal Flow Sensing for Schooling Swimmerscites workP2860

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