2022 IEEE World AI IoT Congress (AIIoT)
2022 IEEE World AI IoT Congress (AIIoT), 06-09 June 2022, Seattle, Wa, USA
Generative adversarial networks (GANs) have become very popular in recent years. GANs have proved to be successful in different computer vision tasks including image-translation, image super-resolution etc. In this paper, we have used GAN models for ship deck segmentation. We have used 2D scanned raster images of ship decks provided by US Navy Military Sealift Command (MSC) to extract necessary information including ship walls, objects etc. Our segmentation results will be helpful to get vector and 3D image of a ship that can be later used for maintenance of the ship. We applied the trained models to engineering documents provided by MSC and obtained very promising results, demonstrating that GANs can be potentially good candidates for this research area.
Original Publication Citation
Uddin, M. S. U., Pamie-George, R., Wilkins, D., Sousa-Poza, A., Canan, M., Kovacic, S., & Li, J. (2022). In 2022 IEEE World AI IoT Congress (AIIoT) (pp. 207-212). IEEE. http://dx.doi.org/10.1109/AIIoT54504.2022.9817355
Shahab Uddin, Mohammad; Pamie-George, Raphael; Wilkins, Daron; Poza, Andres Sousa; Canan, Mustafa; Kovacic, Samuel; and Li, Jiang, "Ship Deck Segmentation in Engineering Document Using Generative Adversarial Networks" (2021). Engineering Management & Systems Engineering Faculty Publications. 136.