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September 10, 2025The Journal of the Acoustical Society of America

Vehicle detection and classification using acoustic and seismic data

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Authors

ABAbdoulaye BarryMDMax Denis

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Overview

Classification algorithms based on acoustic and seismic data demonstrate high accuracy in vehicle detection.

Key Points

  • The KNN model achieved the highest classification accuracy of 99.76%, outperforming other models.
  • Acoustic and seismic data were effectively analyzed using machine learning techniques like CNN and SVM.
  • The SVM, KNN, and CNN models showed promising results, with accuracies above 98% in vehicle classification.
  • These findings indicate that acoustic and seismic data can significantly enhance vehicle detection systems.

Cite This Study

Barry et al. (2025) studied this question.

synapsesocial.com/papers/68c1b5fe54b1d3bfb60ea9ffhttps://doi.org/10.1121/10.0038316
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Also Consider

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  1. 1Vehicle Detection and Classification with Compact Sensor Technologies and Convolutional Neural Networks2026
  2. 2Identifying Vehicle Signals in Continuous Seismic Data Using Unsupervised Machine-Learning Techniques2025
  3. 3Identifying Vehicle Signals in Continuous Seismic Data Using Unsupervised Machine-Learning Techniques2025 · 1 citations
  4. 4Acoustic Vehicle Classification using Deep Learning Trained on a Spectrogram and Scalogram Fusion2024 · 1 citations
  5. 5Exploring Classification of Vehicles Using Horn Sound Analysis: A Deep Learning-Based Approach2024 · 8 citations