26.1.12.1 Noise from Ships, Vehicles, Analyze the Sounds

Chapter Contents (Back)
Acoustic. Ship Noise. Vehicle Noise. Sonar. Hydrophone. Audio.
See also ATR -- Sonar, Acoustic, Hydrophone.

Thomas, D.W., Wilkins, B.R.,
The analysis of vehicle sounds for recognition,
PR(4), No. 4, December 1972, pp. 379-389.
Elsevier DOI 0309
BibRef

Huang, W.[Wei], Wang, D.[Delin], Garcia, H.[Heriberto], Godø, O.R.[Olav Rune], Ratilal, P.[Purnima],
Continental Shelf-Scale Passive Acoustic Detection and Characterization of Diesel-Electric Ships Using a Coherent Hydrophone Array,
RS(9), No. 8, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Cao, J., Wang, W., Wang, J., Wang, R.,
Excavation Equipment Recognition Based on Novel Acoustic Statistical Features,
Cyber(47), No. 12, December 2017, pp. 4392-4404.
IEEE DOI 1712
Acoustics, Engines, Monitoring, Performance evaluation, Pipelines, Support vector machines, Vehicles, Acoustic statistical feature, extreme learning machine BibRef

Zhu, C.Y.[Chen-Yang], Garcia, H.[Heriberto], Kaplan, A.[Anna], Schinault, M.[Matthew], Handegard, N.O.[Nils Olav], Godø, O.R.[Olav Rune], Huang, W.[Wei], Ratilal, P.[Purnima],
Detection, Localization and Classification of Multiple Mechanized Ocean Vessels over Continental-Shelf Scale Regions with Passive Ocean Acoustic Waveguide Remote Sensing,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812
BibRef

Zhou, X.Y.[Xing-Yue], Yang, K.[Kunde], Duan, R.[Rui],
Deep Learning Based on Striation Images for Underwater and Surface Target Classification,
SPLetters(26), No. 9, September 2019, pp. 1378-1382.
IEEE DOI 1909
belief networks, convolutional neural nets, image classification, interference (signal), learning (artificial intelligence), sonar images BibRef

Zhu, C.Y.[Chen-Yang], Seri, S.G.[Sai Geetha], Mohebbi-Kalkhoran, H.[Hamed], Ratilal, P.[Purnima],
Long-Range Automatic Detection, Acoustic Signature Characterization and Bearing-Time Estimation of Multiple Ships with Coherent Hydrophone Array,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link 2011
BibRef

He, L.[Lei], Shen, X.H.[Xiao-Hong], Zhang, M.H.[Mu-Hang], Wang, H.Y.[Hai-Yan],
Discriminative Ensemble Loss for Deep Neural Network on Classification of Ship-Radiated Noise,
SPLetters(28), 2021, pp. 449-453.
IEEE DOI 2103
Neural networks, Measurement, Boats, Training, Loss measurement, Weight measurement, ship-radiated noise BibRef

Kumar, M.L.N.[Murala Laxmi Naresh], Sen, D.[Debarati], Mohine, S.[Shailesh], Bansod, B.S.[Babankumar S.], Bhalla, R.[Rakesh], Basra, A.[Anshul],
Acoustic Modality Based Hybrid Deep 1D CNN-BiLSTM Algorithm for Moving Vehicle Classification,
ITS(23), No. 9, September 2022, pp. 16206-16216.
IEEE DOI 2209
Feature extraction, Convolutional neural networks, Support vector machines, Acoustics, Kernel, Convolution, vehicle classification BibRef

Wang, C.Y.[Chao-Yi], Song, Y.Z.[Yao-Zhe], Liu, H.L.[Hao-Long], Liu, H.W.[Hua-Wei], Liu, J.[Jianpo], Li, B.Q.[Bao-Qing], Yuan, X.B.[Xia-Bing],
Real-Time Vehicle Sound Detection System Based on Depthwise Separable Convolution Neural Network and Spectrogram Augmentation,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
BibRef

Zhu, S.[Shan], Zhang, G.J.[Guo-Jun], Wu, D.[Daiyue], Jia, L.[Li], Zhang, Y.F.[Yi-Fan], Geng, Y.[Yanan], Liu, Y.[Yan], Ren, W.R.[Wei-Rong], Zhang, W.D.[Wen-Dong],
High Signal-to-Noise Ratio MEMS Noise Listener for Ship Noise Detection,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
BibRef

Liu, S.[Shuai], Fu, X.M.[Xiao-Mei], Xu, H.[Hong], Zhang, J.L.[Jia-Li], Zhang, A.[Anmin], Zhou, Q.J.[Qing-Ji], Zhang, H.[Hao],
A Fine-Grained Ship-Radiated Noise Recognition System Using Deep Hybrid Neural Networks with Multi-Scale Features,
RS(15), No. 8, 2023, pp. 2068.
DOI Link 2305
BibRef

Li, Y.X.[Yu-Xing], Liang, L.[Lili], Zhang, S.[Shuai],
Hierarchical Refined Composite Multi-Scale Fractal Dimension and Its Application in Feature Extraction of Ship-Radiated Noise,
RS(15), No. 13, 2023, pp. 3406.
DOI Link 2307
BibRef

Song, R.P.[Rui-Ping], Feng, X.[Xiao], Wang, J.F.[Jun-Feng], Sun, H.X.[Hai-Xin], Zhou, M.Z.[Ming-Zhang], Esmaiel, H.[Hamada],
Underwater Acoustic Nonlinear Blind Ship Noise Separation Using Recurrent Attention Neural Networks,
RS(16), No. 4, 2024, pp. 653.
DOI Link 2402
BibRef

Thomas, P.J.[Peter J.], Heggelund, Y.[Yngve], Klepsvik, I.[Inge], Cook, J.[Jeremy], Kolltveit, E.[Erling], Vaa, T.[Torgeir],
The Performance of Distributed Acoustic Sensing for Tracking the Movement of Road Vehicles,
ITS(25), No. 6, June 2024, pp. 4933-4946.
IEEE DOI 2406
Roads, Optical fiber sensors, Optical fiber cables, Optical fibers, Backscatter, Signal to noise ratio, Radar, Distributed sensing, traffic monitoring BibRef


Wang, L., Cavallaro, A.,
Ear in the sky: Ego-noise reduction for auditory micro aerial vehicles,
AVSS16(152-158)
IEEE DOI 1611
Correlation BibRef

Borodina, E.L., Gorskaya, N.V., Gorsky, S.M., Khil'ko, A.I., Shirokov, V.N.,
Tomographical acoustic vision in the ocean,
ICIP94(I: 900-904).
IEEE DOI 9411
BibRef

Chapter on New Unsorted Entries, and Other Miscellaneous Papers continues in
Binaural Audio, Stereophonic Sound .


Last update:Sep 30, 2026 at 11:45:00