{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T23:35:32Z","timestamp":1764977732308,"version":"3.46.0"},"reference-count":41,"publisher":"Walter de Gruyter GmbH","issue":"1","license":[{"start":{"date-parts":[[2017,7,22]],"date-time":"2017-07-22T00:00:00Z","timestamp":1500681600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/3.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61301241","61602229","61403353","61501417","61271405"],"award-info":[{"award-number":["61301241","61602229","61403353","61501417","61271405"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2016M590659"],"award-info":[{"award-number":["2016M590659"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,1,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Research on internal waves in the coastal ocean is one of the most important tasks both in physical oceanography and ocean monitoring network. Currently, how to quickly and accurately detect the ocean internal waves from the huge ocean surface is still a challenging issue. In this paper, we model the ocean internal wave detection as a task of region classification for texture images and then propose a rapid internal waves detection method based on a deep learning framework (PCANet). In the proposed method, two models have been trained: one is the deep feature representation model, which combines principal component analysis (PCA), binary hashing, and block-wise histograms and can extract more distinguishing features than handcraft feature. Moreover, because the filter learning in PCANet does not require regularized parameters and numerical optimization solver, the training process of the representation model is very fast. The other one is a classification model based on a linear support vector machine. The object proposal method has been applied to get the possible candidates when analyzing a captured image, which dramatically decreases the searching time. Experiment results on the data set captured by unmanned aerial vehicles verify the speed ability and effectiveness of the proposed method.<\/jats:p>","DOI":"10.1515\/jisys-2017-0033","type":"journal-article","created":{"date-parts":[[2017,7,23]],"date-time":"2017-07-23T06:01:07Z","timestamp":1500789667000},"page":"103-113","source":"Crossref","is-referenced-by-count":11,"title":["A Fast Internal Wave Detection Method Based on PCANet for Ocean Monitoring"],"prefix":"10.1515","volume":"28","author":[{"given":"Shengke","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Computer Science and Technology , Ocean University of China , Qingdao , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qinghong","family":"Dong","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology , Ocean University of China , Qingdao , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lianghua","family":"Duan","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology , Ocean University of China , Qingdao , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yujuan","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Information and Electrical Engineering , Ludong University , Yantai , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Muwei","family":"Jian","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology , Ocean University of China , Qingdao , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianzhong","family":"Li","sequence":"additional","affiliation":[{"name":"College of Mathematics and Statistics , Hanshan Normal University , Chaozhou , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junyu","family":"Dong","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology , Ocean University of China , Qingdao , China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2017,7,22]]},"reference":[{"key":"2025120523301811041_j_jisys-2017-0033_ref_001_w2aab3b7b8b1b6b1ab1b5b1Aa","doi-asserted-by":"crossref","unstructured":"W. Alpers, Theory of radar imaging of internal waves, Nature314 (1985), 245\u2013247.10.1038\/314245a0","DOI":"10.1038\/314245a0"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_002_w2aab3b7b8b1b6b1ab1b5b2Aa","doi-asserted-by":"crossref","unstructured":"W. Alpers, Ocean internal waves, in: Encyclopedia of Remote Sensing, pp. 433\u2013437, Springer, 2014.","DOI":"10.1007\/978-0-387-36699-9_118"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_003_w2aab3b7b8b1b6b1ab1b5b3Aa","doi-asserted-by":"crossref","unstructured":"K. Anderson and K. J. Gaston, Lightweight unmanned aerial vehicles will revolutionize spatial ecology, Front. Ecol. Environ.11 (2013), 138\u2013146.10.1890\/120150","DOI":"10.1890\/120150"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_004_w2aab3b7b8b1b6b1ab1b5b4Aa","doi-asserted-by":"crossref","unstructured":"T. B. Benjamin, Internal waves of finite amplitude and permanent form, J. Fluid Mech.25 (1966), 241\u2013270.10.1017\/S0022112066001630","DOI":"10.1017\/S0022112066001630"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_005_w2aab3b7b8b1b6b1ab1b5b5Aa","doi-asserted-by":"crossref","unstructured":"E. H. Boak and I. L. Turner, Shoreline definition and detection: a review, J. Coastal Res.21 (2005), 688\u2013703.","DOI":"10.2112\/03-0071.1"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_006_w2aab3b7b8b1b6b1ab1b5b6Aa","unstructured":"S. Q. Cai, W. J. Zhang and S. A. Wang, An advance in marine environment observation technology, J. Trop. Oceanogr.26 (2007), 76\u201381."},{"key":"2025120523301811041_j_jisys-2017-0033_ref_007_w2aab3b7b8b1b6b1ab1b5b7Aa","unstructured":"A. Cavoukian, Privacy and drones: unmanned aerial vehicles, Information and Privacy Commissioner of Ontario, Canada Ontario, Canada, 2012."},{"key":"2025120523301811041_j_jisys-2017-0033_ref_008_w2aab3b7b8b1b6b1ab1b5b8Aa","doi-asserted-by":"crossref","unstructured":"L. R.Centurioni, Observations of large-amplitude nonlinear internal waves from a drifting array: instruments and methods. J. Atmos. Ocean. Tech.27 (2010), 1711\u20131731.10.1175\/2010JTECHO774.1","DOI":"10.1175\/2010JTECHO774.1"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_009_w2aab3b7b8b1b6b1ab1b5b9Aa","doi-asserted-by":"crossref","unstructured":"T. H. Chan, K. Jia, S. Gao and J. Lu, PCANet: a simple deep learning baseline for image classification? IEEE Trans. Image Process.24 (2015), 5017\u20135032.10.1109\/TIP.2015.2475625","DOI":"10.1109\/TIP.2015.2475625"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_010_w2aab3b7b8b1b6b1ab1b5c10Aa","doi-asserted-by":"crossref","unstructured":"C.-Y. Chen, J. R.-C. Hsu, M.-H. Cheng, H.-H. Chen and C.-F. Kuo, An investigation on internal solitary waves in a two-layer fluid: propagation and reflection from steep slopes, Ocean Eng.34 (2007), 171\u2013184.10.1016\/j.oceaneng.2005.11.020","DOI":"10.1016\/j.oceaneng.2005.11.020"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_011_w2aab3b7b8b1b6b1ab1b5c11Aa","doi-asserted-by":"crossref","unstructured":"W. Choi and R. Camassa, Fully nonlinear internal waves in a two-fluid system, J. Fluid Mech.396 (1996), 1\u201336.","DOI":"10.1017\/S0022112099005820"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_012_w2aab3b7b8b1b6b1ab1b5c12Aa","doi-asserted-by":"crossref","unstructured":"R. Cristi, F. A. Papoulias and A. J. Healey, Adaptive sliding mode control of autonomous underwater vehicles in the dive plane, IEEE J. Oceanic Eng.15 (1990), 152\u2013160.10.1109\/48.107143","DOI":"10.1109\/48.107143"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_013_w2aab3b7b8b1b6b1ab1b5c13Aa","doi-asserted-by":"crossref","unstructured":"X. Gan, W. Huang, J. Yang and B. Fu, Internal wave packet characterization from SAR images using empirical mode decomposition (emd), in: Image and Signal Processing, 2008. CISP\u201908. Congress on, vol. 4, pp. 750\u2013753, IEEE, 2008.","DOI":"10.1109\/CISP.2008.136"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_014_w2aab3b7b8b1b6b1ab1b5c14Aa","doi-asserted-by":"crossref","unstructured":"C. Garrett and W. Munk, Space-time scales of internal waves, Geophys. Astro. Fluid Dyn.3 (1972), 225\u2013264.10.1080\/03091927208236082","DOI":"10.1080\/03091927208236082"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_015_w2aab3b7b8b1b6b1ab1b5c15Aa","doi-asserted-by":"crossref","unstructured":"C. Garrett and W. Munk, Internal waves in the ocean, Annu. Rev. Fluid Mech.11 (1979), 339\u2013369.10.1146\/annurev.fl.11.010179.002011","DOI":"10.1146\/annurev.fl.11.010179.002011"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_016_w2aab3b7b8b1b6b1ab1b5c16Aa","doi-asserted-by":"crossref","unstructured":"R. Girshick, Fast R-CNN, in: IEEE International Conference on Computer Vision, pp. 1440\u20131448, 2015.","DOI":"10.1109\/ICCV.2015.169"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_017_w2aab3b7b8b1b6b1ab1b5c17Aa","doi-asserted-by":"crossref","unstructured":"R. Girshick, J. Donahue, T. Darrell and J. Malik, Rich feature hierarchies for accurate object detection and semantic segmentation. Comput. Sci. (2014), 580\u2013587.","DOI":"10.1109\/CVPR.2014.81"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_018_w2aab3b7b8b1b6b1ab1b5c18Aa","doi-asserted-by":"crossref","unstructured":"R. Girshick, J. Donahue, T. Darrell and J. Malik, Region-based convolutional networks for accurate object detection and segmentation. IEEE Trans. Pattern Anal. Mach. Intell.38 (2016), 142\u2013158.10.1109\/TPAMI.2015.2437384","DOI":"10.1109\/TPAMI.2015.2437384"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_019_w2aab3b7b8b1b6b1ab1b5c19Aa","doi-asserted-by":"crossref","unstructured":"R. Grimshaw, K. R. Helfrich and E. R. Johnson. Experimental study of the effect of rotation on nonlinear internal waves, Phys. Fluids25 (2013), 1\u201327.","DOI":"10.1063\/1.4805092"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_020_w2aab3b7b8b1b6b1ab1b5c20Aa","doi-asserted-by":"crossref","unstructured":"J. Grue, A. Jensen, P.-O. Rus\u00e5s and J. K. Sveen, Properties of large-amplitude internal waves. J. Fluid Mech.380 (1999), 257\u2013278.10.1017\/S0022112098003528","DOI":"10.1017\/S0022112098003528"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_021_w2aab3b7b8b1b6b1ab1b5c21Aa","doi-asserted-by":"crossref","unstructured":"C. C. Kao, L. H. Lee, C. C. Tai and Y. C. Wei, Extracting the ocean surface feature of non-linear internal solitary waves in modis satellite images, in: International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp. 27\u201330, 2007.","DOI":"10.1109\/IIHMSP.2007.4457485"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_022_w2aab3b7b8b1b6b1ab1b5c22Aa","doi-asserted-by":"crossref","unstructured":"C. G. Koop and G. Butler, An investigation of internal solitary waves in a two-fluid system, J. Fluid Mech.112 (1981), 225\u2013251.10.1017\/S0022112081000372","DOI":"10.1017\/S0022112081000372"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_023_w2aab3b7b8b1b6b1ab1b5c23Aa","doi-asserted-by":"crossref","unstructured":"I. Kozlov, D. Romanenkov, A. Zimin and B. Chapron, SAR observing large-scale nonlinear internal waves in the white sea. Remote Sens. Environ.147 (2014), 99\u2013107.10.1016\/j.rse.2014.02.017","DOI":"10.1016\/j.rse.2014.02.017"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_024_w2aab3b7b8b1b6b1ab1b5c24Aa","doi-asserted-by":"crossref","unstructured":"J. Li, X. Chen, M. Li, J. Li, P. P. C. Lee and W. Lou, Secure deduplication with efficient and reliable convergent key management, IEEE Trans. Parall. Distr. Syst.25 (2014), 1615\u20131625.10.1109\/TPDS.2013.284","DOI":"10.1109\/TPDS.2013.284"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_025_w2aab3b7b8b1b6b1ab1b5c25Aa","doi-asserted-by":"crossref","unstructured":"J. Li, J. Li, X. Chen, C. Jia and W. Lou, Identity-based encryption with outsourced revocation in cloud computing, IEEE Trans. Comput.64 (2015), 425\u2013437.10.1109\/TC.2013.208","DOI":"10.1109\/TC.2013.208"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_026_w2aab3b7b8b1b6b1ab1b5c26Aa","doi-asserted-by":"crossref","unstructured":"A. K. Liu, Y. S. Chang, M. K. Hsu and N. K. Liang, Evolution of nonlinear internal waves in the East and South China Seas, J. Geophys. Res. Atmos.103 (1998), 7995\u20138008.10.1029\/97JC01918","DOI":"10.1029\/97JC01918"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_027_w2aab3b7b8b1b6b1ab1b5c27Aa","doi-asserted-by":"crossref","unstructured":"W. Liu, D. Anguelov, D. Erhan, C. Szegedy, S. Reed, C. Y. Fu and A. C. Berg, SSD: single shot multibox detector, in: Proceedings of the European Conference on Computer Vision, 2016.","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_028_w2aab3b7b8b1b6b1ab1b5c28Aa","doi-asserted-by":"crossref","unstructured":"A. R. Osborne, T. L. Burch, R. I. Scarlet, The influence of internal waves on deep-water drilling, J. Petrol. Technol.30 (1978), 1\u2013497.","DOI":"10.2118\/6913-PA"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_029_w2aab3b7b8b1b6b1ab1b5c29Aa","doi-asserted-by":"crossref","unstructured":"L. Ostrovsky, E. Pelinovsky, V. Shrira and Y. Stepanyants, Beyond the KdV: post-explosion development. Chaos25 (2015), 097620.10.1063\/1.4927448","DOI":"10.1063\/1.4927448"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_030_w2aab3b7b8b1b6b1ab1b5c30Aa","unstructured":"S. Ren, K. He, R. Girshick and J. Sun, Faster R-CNN: towards real-time object detection with region proposal networks, In: Adv. Neural Inform. Process. Syst. (2015), 91\u201399."},{"key":"2025120523301811041_j_jisys-2017-0033_ref_031_w2aab3b7b8b1b6b1ab1b5c31Aa","doi-asserted-by":"crossref","unstructured":"J. A. Rodenas and R. Garello, Wavelet analysis in SAR ocean image profiles for internal wave detection and wavelength estimation. IEEE Trans. Geosci. Remote Sensing.35 (1997), 933\u2013945.10.1109\/36.602535","DOI":"10.1109\/36.602535"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_032_w2aab3b7b8b1b6b1ab1b5c32Aa","doi-asserted-by":"crossref","unstructured":"J. A. R\u00f3denas and R. Garello, Internal wave detection and location in SAR images using wavelet transform. IEEE Trans. Geosci. Remote Sensing36 (1998), 1494\u20131507.10.1109\/36.718853","DOI":"10.1109\/36.718853"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_033_w2aab3b7b8b1b6b1ab1b5c33Aa","doi-asserted-by":"crossref","unstructured":"S. Roy, P. Arabshahi, R. Dan and W. Fox, Wide area ocean networks: architecture and system design considerations, in: Wuwnet06 Los, (2015), 25\u201332.","DOI":"10.1145\/1161039.1161046"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_034_w2aab3b7b8b1b6b1ab1b5c34Aa","doi-asserted-by":"crossref","unstructured":"E. Shi and A. Perrig, Designing secure sensor networks, IEEE Wireless Commun.11 (2004), 38\u201343.10.1109\/MWC.2004.1368895","DOI":"10.1109\/MWC.2004.1368895"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_035_w2aab3b7b8b1b6b1ab1b5c35Aa","doi-asserted-by":"crossref","unstructured":"J. Small, Z. Hallock, G. Pavey and J. Scott, Observations of large amplitude internal waves at the Malin Shelf edge during SESAME 1995. Cont. Shelf Res.19 (1999), 1389\u20131436.10.1016\/S0278-4343(99)00023-0","DOI":"10.1016\/S0278-4343(99)00023-0"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_036_w2aab3b7b8b1b6b1ab1b5c36Aa","doi-asserted-by":"crossref","unstructured":"Z. Sun, R. Zhang and J. Yan, The influence of internal waves on signal fluctuation in the yellow sea, J. Acoust. Soc. Am.105 (1999), 1311\u20131311.10.1121\/1.424781","DOI":"10.1121\/1.424781"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_037_w2aab3b7b8b1b6b1ab1b5c37Aa","unstructured":"C. Szegedy, A. Toshev and D. Erhan, Deep neural networks for object detection. Adv. Neural Inform. Process. Syst.26 (2013), 2553\u20132561."},{"key":"2025120523301811041_j_jisys-2017-0033_ref_038_w2aab3b7b8b1b6b1ab1b5c38Aa","unstructured":"S. Tharawechrak, In-situ observations of internal waves on the continental slope and shelf of the south china sea, MSc thesis, Florida State University, 2007."},{"key":"2025120523301811041_j_jisys-2017-0033_ref_039_w2aab3b7b8b1b6b1ab1b5c39Aa","doi-asserted-by":"crossref","unstructured":"J. R. R. Uijlings, K. E. A. Van De Sande, T. Gevers and A. W. M. Smeulders, Selective search for object recognition, Int. J. Comput. Vision104 (2013), 154\u2013171.10.1007\/s11263-013-0620-5","DOI":"10.1007\/s11263-013-0620-5"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_040_w2aab3b7b8b1b6b1ab1b5c40Aa","doi-asserted-by":"crossref","unstructured":"K. P. Valavanis and G. J. Vachtsevanos, Handbook of Unmanned Aerial Vehicles, Springer, Netherlands, 2015.","DOI":"10.1007\/978-90-481-9707-1"},{"key":"2025120523301811041_j_jisys-2017-0033_ref_041_w2aab3b7b8b1b6b1ab1b5c41Aa","doi-asserted-by":"crossref","unstructured":"R. B. Wynn, V. A. I. Huvenne, T. P. Le Bas, B. J. Murton, D. P. Connelly, B. J. Bett, H. A. Ruhl, K. J. Morris, J. Peakall and D. R. Parsons, Autonomous underwater vehicles (AUVs): their past, present and future contributions to the advancement of marine geoscience, Mar. Geol.352 (2014), 451\u2013468.10.1016\/j.margeo.2014.03.012","DOI":"10.1016\/j.margeo.2014.03.012"}],"container-title":["Journal of Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.degruyter.com\/view\/j\/jisys.2019.28.issue-1\/jisys-2017-0033\/jisys-2017-0033.xml","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyterbrill.com\/document\/doi\/10.1515\/jisys-2017-0033\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyterbrill.com\/document\/doi\/10.1515\/jisys-2017-0033\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T23:30:35Z","timestamp":1764977435000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.degruyterbrill.com\/document\/doi\/10.1515\/jisys-2017-0033\/html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,7,22]]},"references-count":41,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2017,7,20]]},"published-print":{"date-parts":[[2019,1,28]]}},"alternative-id":["10.1515\/jisys-2017-0033"],"URL":"https:\/\/doi.org\/10.1515\/jisys-2017-0033","relation":{},"ISSN":["2191-026X","0334-1860"],"issn-type":[{"type":"electronic","value":"2191-026X"},{"type":"print","value":"0334-1860"}],"subject":[],"published":{"date-parts":[[2017,7,22]]}}}