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Application of Convolutional Neural Network (CNN) to Recognize Ship Structures.

Jae-Jun LimDae-Won KimWoon-Hee HongMin KimDong-Hoon LeeSun-Young KimJae-Hoon Jeong
Published in: Sensors (Basel, Switzerland) (2022)
The purpose of this paper is to study the recognition of ships and their structures to improve the safety of drone operations engaged in shore-to-ship drone delivery service. This study has developed a system that can distinguish between ships and their structures by using a convolutional neural network (CNN). First, the dataset of the Marine Traffic Management Net is described and CNN's object sensing based on the Detectron2 platform is discussed. There will also be a description of the experiment and performance. In addition, this study has been conducted based on actual drone delivery operations-the first air delivery service by drones in Korea.
Keyphrases
  • convolutional neural network
  • deep learning
  • healthcare
  • mental health
  • high throughput