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  • 中文期刊(566297)
  • 外文期刊(3)
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期刊名称

  • applied sciences-basel(1)
  • ecological indicators(1)
  • peerj computer science(1)

关键词

  • geohash; vessel trajectory; deep convolutional neural network; deep learning; spatiotemporal context; fishing operation type; embedding(1)
  • identification of lit fishing vessel; deep learning; yolo-v5; object detection(1)
  • ship rescue; effective rescue time; gridding; ship position code; neighborhood search; nearest neighbor search; google s2(1)

作者

  • Jiang, Bohui AND Zhou, Weifeng AND Jiang, Bohui(0)

机构

  • shanghai ocean univ, coll marine sci, shanghai 201306, peoples r china(2)
  • chinese acad fishery sci, east china sea fisheries res inst, shanghai 200090, peoples r china(1)
  • chinese acad fishery sci, east china sea fisheries res inst, shanghai, peoples r china(1)
  • chinese acad fishery sci, east china sea fishery res inst, shanghai 200090, peoples r china(1)
  • shanghai ocean univ, shanghai, peoples r china(1)

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年份

  • 2025(1)
  • 2024(2)
科研产出
资源类型: 外文期刊
作者:Jiang, Bohui(精确检索)
作者:Zhou, Weifeng(精确检索)
作者:Jiang, Bohui(精确检索)
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共3条记录
1Storage and Management of Ship Position Based on Geographic Grid Coding and Its Efficiency Analysis in Neighborhood Search-A Case Study of Shipwreck Rescue and Google S2

作者：

机构：

来源：APPLIED SCIENCES-BASEL

关键词： ship rescue; effective rescue time; gridding; ship position code; neighborhood search; nearest neighbor search; Google S2

年份：2024

2Exploring deep learning techniques for the extraction of lit fishing vessels from Luojia1-01

作者：

机构：

来源：ECOLOGICAL INDICATORS

关键词： Identification of lit fishing vessel; Deep learning; YOLO-V5; Object detection

年份：2024

3Fishing operation type recognition based on multi-branch convolutional neural network using trajectory data

作者：

机构：

来源：PEERJ COMPUTER SCIENCE

关键词： Geohash; Vessel trajectory; Deep convolutional neural network; Deep learning; Spatiotemporal context; Fishing operation type; Embedding

年份：2025

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