|
04. Comprehensive Nuclear-Test-Ban Treaty Monitoring, and its Civil and Scientific Applications |
Decadal observations of deep ocean temperature change passively probed with acoustic waves
|
Läslo Evers |
|
04. Comprehensive Nuclear-Test-Ban Treaty Monitoring, and its Civil and Scientific Applications |
In-water explosions recorded at the IMS hydrophone network from natural and anthropogenic events
|
Tiago Oliveira, Mark Prior |
|
04. Comprehensive Nuclear-Test-Ban Treaty Monitoring, and its Civil and Scientific Applications |
Vertical-mode and horizontal-ray modeling of T waves from the 2020 Beirut-port explosion
|
Jean Lecoulant, Abdel-Ouahab Boudraa |
|
04. Comprehensive Nuclear-Test-Ban Treaty Monitoring, and its Civil and Scientific Applications |
Hydroacoustic waves detected by an interferometry-based fiber optic strainmeter from a series of submarine earthquakes near Torishima Island, Japan
|
Hiroyuki Matsumoto, Mario Zampolli, Eiichiro Araki, Georgios Haralabus |
|
04. Comprehensive Nuclear-Test-Ban Treaty Monitoring, and its Civil and Scientific Applications |
A study of changes in vocalization frequency of Antarctic blue whales and fin whales recorded at CTBTO hydroacoustic stations
|
Stephen Robinson, Peter Harris, Michael Ainslie, Peter Tyack, Michele Halvorsen, Alex MacGillivray, Lian Wang, Valerie Livina |
|
04. Comprehensive Nuclear-Test-Ban Treaty Monitoring, and its Civil and Scientific Applications |
Interpretation of fin whales diving behaviour in the vicinity of an IMS hydrophone triplet
|
Ronan Le Bras, Peter Nielsen, Paulina Bittner |
|
04. Comprehensive Nuclear-Test-Ban Treaty Monitoring, and its Civil and Scientific Applications |
Transmission of the explosive sound in the shallow-water wedge and along a flat bottom of the deep ocean
|
Piotr Borejko |
|
05. Distributed Fiber-Optic Sensing technology for underwater acoustical monitoring |
Analysis of passive DAS data for observation of microseisms and extracting Scholte wave dispersion in shallow water
|
Hefeng Dong, Michael Taroudakis |
|
05. Distributed Fiber-Optic Sensing technology for underwater acoustical monitoring |
Detection and tracking of baleen whales using a subsea telecommunication cable on the Northwest Shelf of Australia
|
Evgenii Sidenko, Alexander Gavrilov, Christine Erbe, Olivia Collet, Boris Gurevich, Henry Debens, Denise McCorry, Roman Pevzner |
|
05. Distributed Fiber-Optic Sensing technology for underwater acoustical monitoring |
Comparison of Detection Methods for Fin Whale Calls from Distributed Acoustic Sensing
|
Khanh Truong, Jo Eidsvik, Robin Andre Rørstadbotnen, Jan Petter Morten |
|
05. Distributed Fiber-Optic Sensing technology for underwater acoustical monitoring |
Deep Learning Approach to Remove Distributed Acoustic Sensing Instrumental Noise
|
Olivia Collet, Xihao Gu, Roman Isaenkov, Evgenii Sidenko, Pavel Shashkin, Roman Pevzner, Konstantin Tertyshnikov, Boris Gurevich, Christine Erbe, Sasha Gavrilov |
|
05. Distributed Fiber-Optic Sensing technology for underwater acoustical monitoring |
DAS reception of acoustic communications from an AUV
|
John POTTER, Simon Hagen Hoff, Emil Wengle, Sebastian Sikora |
|
06. Enhancing underwater acoustic sensing through machine learning |
Neural Network-Informed Acoustics Sensors for Optimal Coherent Processing: Benchmarking in a Forward-Modelled Fluctuating Ocean Environment
|
Antoine Blachet, Xavier Cristol, Thomas Mahiout, Dominique Fattaccioli, Gaultier Real |
|
06. Enhancing underwater acoustic sensing through machine learning |
The urgent call on data management: are we capable to store valuable (meta)data for naval application?
|
Sonia Papili |
|
06. Enhancing underwater acoustic sensing through machine learning |
Power and accuracy trade-offs for machine learning methods applied to detection of underwater sound sources
|
William Butler, Harrison Smith, Marios Impraimakis, Andrew Barnes, Alan Hunter |
|
06. Enhancing underwater acoustic sensing through machine learning |
An Investigation of Machine Learning Capabilities for Cavitation Detection
|
Dale Smith, Oscar Carter |
|
06. Enhancing underwater acoustic sensing through machine learning |
Spatial-frequency sparse adaptive learning for enhancing tonals in impulse noise
|
Fengdan Jiang, Cheng Chi, Chonglei Liu, Guanqun Wang, Shenglong Jin, Yu Li, Haining Huang |
|
06. Enhancing underwater acoustic sensing through machine learning |
Physics-informed neural networks (PINNs) for underwater acoustic propagation modeling: A review
|
Peng Xiao, Yuxiang Gao, Zhenglin Li |
|
06. Enhancing underwater acoustic sensing through machine learning |
Phase-Feature-Based Deep Learning Method for Target Depth Discrimination in Shallow-Water Environments
|
Qianyan Li, Wenbo Wang, QUNYAN Ren, Li Ma |
|
06. Enhancing underwater acoustic sensing through machine learning |
Advancing a Passive Acoustic Simulation to Research Empathetic Artificial Intelligence (EAI) in Human-AI Teaming
|
Madalin Facino, Alan Hunter, Christof Lutteroth, Aaron Roberts, Samantha Dugelay |