ASMSP-L1.3
Uncertainty Quantification for Acoustic-Based Drone Detection and Localization under Adverse Noise Conditions
Özkan Çaylı, Pei Xiao, Wenwu Wang, University of Surrey, United Kingdom
Session:
Sound Source Localization and Tracking Lecture
Track:
1: ASMSP - Acoustic, Speech and Music Signal Processing
Location:
Concert Hall
Session Time:
Tue, 1 Sep, 10:50 - 12:30
Presentation Time:
Tue, 1 Sep, 11:30 - 11:50
Session Chair:
Sharon Gannot, Bar-Ilan University
Presentation
Discussion
Session ASMSP-L1
ASMSP-L1.1: A STEERED RESPONSE POWER METHOD FOR SOUND SOURCE LOCALIZATION WITH GENERIC ACOUSTIC MODELS
Kaspar Müller, Markus Buck, Cerence AI, Germany; Simon Doclo, University of Oldenburg, Germany; Jan Østergaard, Aalborg University, Denmark; Tobias Wolff, Cerence AI, Germany
ASMSP-L1.2: Localizing multiple sound sources by associating sub-band TDOA features for biodiversity monitoring
Manuel Alejandro Jaramillo-Rodriguez, KU Leuven, Belgium; Randall Ali, University of Surrey, United Kingdom; Toon van Waterschoot, KU Leuven, Belgium
ASMSP-L1.3: Uncertainty Quantification for Acoustic-Based Drone Detection and Localization under Adverse Noise Conditions
Özkan Çaylı, Pei Xiao, Wenwu Wang, University of Surrey, United Kingdom
ASMSP-L1.4: Domain-Robust Sound Source Tracking using Nuisance Disentanglement
Bingxiang Zhong, Stefano Damiano, Thomas Dietzen, KU Leuven, Belgium
ASMSP-L1.5: POINT NEURON EMBEDDED KALMAN FILTER FOR NARROWBAND SOUND SOURCE TRACKING
Vishwanath Vinod, Indian Institute of Technology Madras, India; Shaoheng Xu, Prasanga N. Samarasinghe, Amy Bastine, Thushara D. Abhayapala, The Australian National University, Australia
Resources
No resources available.