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An Efficient and Adaptive Method for Collision Probability of Ships, Icebergs Using CNN and DBSCAN Clustering Algorithm

  • Syed Zishan AliEmail author
  • Monica Makhija
  • Daljeet Choudhary
  • Hitesh Singh
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 985)

Abstract

Collision between ships and icebergs is a major problem in glacial area, where large to small icebergs becomes a threat to cargo ships, tankers, fishing ships etc. In this paper, we have devised a new approach for the detection of icebergs and movement of ships to predict their probability of collision. In this proposed work, an adaptive method is used to detect the presence of icebergs and the velocity of ships, followed by integrating the obtained data and applying the Bayesian algorithm we have successfully computed the collision probability. This work exhibits effective results against reduced visibility due to fog. Besides, we have acquired all the foreground authentic data from valid resources. So, the results will help in marking the safe and unsafe zones in the form of clusters by using DBSCAN algorithm.

Keywords

Ships Icebergs Convolution neural network Collision probability Cluster 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Syed Zishan Ali
    • 1
    Email author
  • Monica Makhija
    • 1
  • Daljeet Choudhary
    • 1
  • Hitesh Singh
    • 1
  1. 1.Bhilai Institute of Technology RaipurRaipurIndia

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