Zihao Sun1,*, Xiao Hu2, Yining Qi2, Yongfeng Huang2, Songbin Li3
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1657-1669, 2023, DOI:10.32604/cmc.2023.036558
Abstract The marine environment is becoming increasingly complex due to the various marine vehicles, and the diversity of maritime objects poses a challenge to marine environmental governance. Maritime object detection technology plays an important role in this segment. In the field of computer vision, there is no sufficiently comprehensive public dataset for maritime objects in the contrast to the automotive application domain. The existing maritime datasets either have no bounding boxes (which are made for object classification) or cover limited varieties of maritime objects. To fulfil the vacancy, this paper proposed the Multi-Category Large-Scale Dataset for Maritime Object Detection (MCMOD) which… More >
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