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20052026
most citedA Review of Vibration-Based Damage Detection in Civil Structures: From Traditional Methods to Machine Learning and Deep Learning Applications

1.4k citations

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12 papers · 1 filter

eess.AS2026

Few-Shot Open-Set Audio Classification Using Attention Information-Fused Prototypes

Yanxiong Li, Jiaxin Tan, Qianqian Li +3

Most existing audio classification methods suppose that each query (testing) sample belongs to a class of support (training) samples, and misrecognize samples of unseen classes as…

eess.AS2026

CNN Models for Microphone Array Covariance Matrix Upsampling and Acoustic Imaging

Marianthi Adamopoulou, Parthasaarathy Sudarsanam, David Diaz-Guerra +5

Acoustic imaging visualization is a core methodology in acoustics, enabling spatial analysis of sound sources and acoustic scenes. However, limited sensor availability in practical…

eess.AS2025

The Spheres Dataset: Multitrack Orchestral Recordings for Music Source Separation and Information Retrieval

Jaime Garcia-Martinez, David Diaz-Guerra, John Anderson +5

This paper introduces The Spheres dataset, multitrack orchestral recordings designed to advance machine learning research in music source separation and related MIR tasks within th…

eess.AS20251 cited

Impact of Microphone Array Mismatches to Learning-based Replay Speech Detection

Michael Neri, Tuomas Virtanen

In this work, we investigate the generalization of a multi-channel learning-based replay speech detector, which employs adaptive beamforming and detection, across different microph…

eess.AS2025

Score-informed Music Source Separation: Improving Synthetic-to-real Generalization in Classical Music

Eetu Tunturi, David Diaz-Guerra, Archontis Politis +1

Music source separation is the task of separating a mixture of instruments into constituent tracks. Music source separation models are typically trained using only audio data, alth…

eess.AS2025

Automatic Live Music Song Identification Using Multi-level Deep Sequence Similarity Learning

Aapo Hakala, Trevor Kincy, Tuomas Virtanen

This paper studies the novel problem of automatic live music song identification, where the goal is, given a live recording of a song, to retrieve the corresponding studio version…