CNN Multibeam Seabed Sediment Classification Combined with a Novel Feature Optimization Method

Author:

Anokye Michael,Cui XiaodongORCID,Yang Fanlin,Fan Miao,Luo Yu,Liu Hongxia

Funder

National Natural Science Foundation of China

Shandong Provincial Natural Science Foundation

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences,Mathematics (miscellaneous)

Reference81 articles.

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2. Anderson JT, Holliday DV, Kloser R, Reid D, Simard Y, Brown CJ, Chapman R, Coggan R, Kieser R, Michaels WL, Orlowski A, Preston J, Simmonds J, Stepnowski A (2007) Ices cooperative research report acoustic seabed classification of marine physical and biological landscapes international council for the exploration of the sea conseil international pour l’exploration de la mer. ICES Cooperative Research Report 183

3. Arel I, Rose DC, Karnowski TP (2010) Deep machine learning-a new frontier in artificial intelligence research [research frontier]. IEEE Comput Intell Mag 5(4):13–18

4. Atallah LN (2004) Learning from sonar data for the classification of underwater seabeds. Ph.D. Thesis, University of Oxford, Oxford, United Kingdom

5. Behera TK, Bakshi S, Nappi M, Sa PK (2023) Superpixel-based multiscale CNN approach towards multiclass object segmentation from UAV-captured aerial images. IEEE J Sel Top Appl Earth Observ Remote Sens 16:1–14. https://doi.org/10.1109/JSTARS.2023.3239119

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