Opto-Electronic Engineering, Volume. 52, Issue 6, 250048(2025)

Ship fine-grained classification of ship targets driven by data and knowledge

Jiasheng Guo1, Jun Liu1、*, Lan He1, Pan Jiang1, Anke Xue1, Yu Gu1, Li Han2, and Jie Zhang2
Author Affiliations
  • 1Key Laboratory of Fundamental Science on Communication Information Transmission and Fusion Technology, Hangzhou Dianzi University, Hangzhou, Zhejiang 310018, China
  • 2China People's Liberation Army 91039 troops, Beijing 102401, China
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    References(31)

    [1] Wang X, Zhang M X. Improving the systems that safeguard China's maritime security[J]. China Secur Stud, 98-117,154(2023).

    [15] Kipf T N, Welling M. Semi-supervised classification with graph convolutional networks[C](2017).

    [29] Cong W L, Ramezani M, Mahdavi M. On provable benefits of depth in training graph convolutional networks[C], 760(2021).

    [31] Clara G, Langer S, Schmidt-Hieber J. Dropout regularization versus ℓ₂-penalization in the linear model[J]. J Mach Learn Res, 25, 1-48(2024).

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    Jiasheng Guo, Jun Liu, Lan He, Pan Jiang, Anke Xue, Yu Gu, Li Han, Jie Zhang. Ship fine-grained classification of ship targets driven by data and knowledge[J]. Opto-Electronic Engineering, 2025, 52(6): 250048

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    Paper Information

    Category: Article

    Received: Feb. 22, 2025

    Accepted: May. 22, 2025

    Published Online: Sep. 3, 2025

    The Author Email: Jun Liu (刘俊)

    DOI:10.12086/oee.2025.250048

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