@article{Autonomous:11120,
      author = {Noel, A and Shreyanka, K and Kumar, KGS and Shameem, BM  and Ashkar, B},
      url = {http://library.imarest.org/record/11120},
      journal = {Conference Proceedings of ICMET},
      title = {Autonomous Ship Navigation Methods: A Review},
      abstract = {Autonomous navigation is achieved by training or  programming the ship with the stored data about the vessel  behavior in various sailing environment. The autonomous  behaviour relies on intelligent analytics based on machine  learning algorithms. As a major advance in machine  learning, the deep learning approach is becoming a powerful  technique for autonomy. The deep learning methodologies are  applied in various fields in the maritime industry such as  detecting anomalies, ship classification, collision  avoidance, risk detection of cyber attacks, navigation in  ports and so on. The present paper reviews on various  methods available in the literature for vessel autonomy and  their applications in ship navigation. The focus of the  work is to illustrate the advantages of deep learning  approach over the machine learning and other traditional  methods.},
      recid = {11120},
      address = {2019-11-05},
}