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Application of Convolutional Neural Network (CNN) to Recognize Ship Structures
- Author(s)
- Lim, Jae-Jun, Kim, Dae-Won, Hong, Woon-Hee, Kim, Min, Lee, Dong-Hoon, Kim, Sun-Young, Jeong, Jae-Hoon
- Issued Date
- 2022-05
- Citation
- SENSORS, v.22, no.10, pp.3824
- Abstract
- 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.
- Publisher
- MDPI
- ISSN
- 1424-8220
- Keyword (Author)
- convolutional neural network (CNN), recognize ship structures, mask R-CNN, faster R-CNN
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