arXiv AI
Jun 17
Explicit Context-Driven Neural Acoustic Modeling for High-Fidelity RIR Generation
arXiv:2509. 15210v2 Announce Type: replace-cross Abstract: Realistic sound simulation plays a critical role in many applications.
Neural Radiated-Noise Fields for Unmanned Underwater Vehicle Noise Spectrum Prediction in Three-Dimensional Scenes
arXiv:2606. 04008v1 Announce Type: cross Abstract: Radiated noise in unmanned underwater vehicles (UUVs) is an important indicator for characterizing acoustic signatures and evaluating platform performance.
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arXiv AI
2d ago
Acoustic UAV Detection in Battlefield Scenarios: Handling Noise, Domain Shift, and Weak Labels
arXiv:2608. 14287v1 Announce Type: cross Abstract: Passive acoustic sensing offers a critical, cost-efficient, and, crucially, passive alternative for detecting small unmanned aerial vehicles.
arXiv AI
Jul 20
Acoustic Imaging for UAV Detection: Dense Beamformed Energy Maps and U-Net SELD
arXiv:2508. 00307v4 Announce Type: replace-cross Abstract: We introduce a U-net model for 360{\deg} acoustic source localization formulated as a spherical semantic segmentation task.
arXiv Machine Learning
Jul 3
CNN Models for Microphone Array Covariance Matrix Upsampling and Acoustic Imaging
arXiv:2607. 01295v1 Announce Type: cross Abstract: Acoustic imaging visualization is a core methodology in acoustics, enabling spatial analysis of sound sources and acoustic scenes.
arXiv Machine Learning
Jul 7
Physics-Informed Domain-Invariant Feature Learning with Autoencoder-Driven Gaussian Clustering for Robust Non-line-of-Sight Scenarios
arXiv:2607. 02537v1 Announce Type: cross Abstract: Jamming and spoofing pose significant threats to wireless and satellite navigation by disrupting radio-frequency (RF) signals and compromising availability and integrity.
arXiv Machine Learning
Jun 2
Parameter-efficient Dual-encoder Architecture with Differentiable Choquet Integral Fusion for Underwater Acoustic Classification
arXiv:2606. 02341v1 Announce Type: cross Abstract: Underwater acoustic classification has a wide array of oceanic applications, but faces challenges due to an increasingly complex acoustic environment.
arXiv AI
Jun 24
Heterogeneous 2D/1D Signal Representation Fusion for Underwater Acoustic Modulation Recognition Under Distribution Shift
arXiv:2606. 23702v1 Announce Type: cross Abstract: Modulation recognition systems rely on heterogeneous signal representations.
arXiv Machine Learning
Jun 24
Neural Posterior Estimation of Terrain Parameters from Radar Sounder Data
arXiv:2605. 08179v2 Announce Type: replace-cross Abstract: Radar sounders are electromagnetic instruments that can probe deep into the subsurface of Earth and other planetary bodies by processing the echo of transmitted radar waves.
arXiv Machine Learning
Aug 11
Physics-Informed Learning for Robust Acoustic Localization with Calibrated Uncertainty
arXiv:2608. 08911v1 Announce Type: cross Abstract: Recent advances in Passive Acoustic Monitoring (PAM) offer an opportunity to obtain ecological spatial point-process data at unprecedented scale.
arXiv AI
Jun 12
Physics-Guided Spatiotemporal Learning for Coastal Wave Peak Period Estimation from Video
arXiv:2606. 13302v1 Announce Type: new Abstract: Wave parameters in the nearshore are crucial for coastal engineering, shoreline protection, marine hazard assessment, and coastal management for climate resilience.
arXiv Machine Learning
Jul 7
Quadrature-Aware Complex-Linear Neural Operator for Boundary-to-Field Prediction in Resonant Acoustics
arXiv:2607. 04407v1 Announce Type: cross Abstract: Repeated prediction of acoustic fields from spatially distributed boundary excitation is computationally expensive when each source realization requires a new wave simulation.
arXiv Machine Learning
1d ago
An Analytical-Prior Framework for Data-Efficient Prediction of Sound-Reduction Frequencies in Rectangular Side-Branch Helmholtz Resonators
arXiv:2608. 16873v1 Announce Type: new Abstract: High-fidelity finite-element simulations can provide accurate numerical predictions for side-branch resonators, but large simulation datasets are expensive to generate and purely data-driven surrogates may become unreliable when simulation-labelled data are scarce.