Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Eric Rigall"'
Publikováno v:
Sensors, Vol 19, Iss 9, p 1985 (2019)
Real-time processing of high-resolution sonar images is of great significance for the autonomy and intelligence of autonomous underwater vehicle (AUV) in complex marine environments. In this paper, we propose a real-time semantic segmentation network
Externí odkaz:
https://doaj.org/article/38b3c0c23ab840ce8082afe6dfd79a5d
Publikováno v:
Sensors, Vol 19, Iss 9, p 2009 (2019)
This paper presents a novel and practical convolutional neural network architecture to implement semantic segmentation for side scan sonar (SSS) image. As a widely used sensor for marine survey, SSS provides higher-resolution images of the seafloor a
Externí odkaz:
https://doaj.org/article/4832eeadf7c74f29aa97c853f071b239
Publikováno v:
Computer Communications. 202:135-144
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 61:1-13
Traditionally, numerical models have been deployed in oceanography studies to simulate ocean dynamics by representing physical equations. However, many factors pertaining to ocean dynamics seem to be ill-defined. We argue that transferring physical k
Autor:
Amanuel Hirpa Madessa, Junyu Dong, Eric Rigall, Qingxuan Lv, Hafiza Sadia Nawaz Nawaz, Israel Mugunga, Shaoxiang Guo
Publikováno v:
IEEE Transactions on Instrumentation and Measurement. 72:1-17
Publikováno v:
IEEE Transactions on Instrumentation and Measurement. 72:1-12
Publikováno v:
IEEE Transactions on Circuits and Systems for Video Technology. 32:5293-5306
Publikováno v:
IEEE Transactions on Circuits and Systems for Video Technology. 32:2303-2314
In recent years, marine animal study has gained increasing research attention, which raises significant demands for fine-grained marine animal segmentation (MAS) techniques. In addition, deep learning has been widely adopted for object segmentation a
Publikováno v:
IEEE Transactions on Circuits and Systems for Video Technology. 32:1552-1563
Textures contain a wealth of image information and are widely used in various fields such as computer graphics and computer vision. With the development of machine learning, the texture synthesis and generation have been greatly improved. As a very c
Publikováno v:
IEEE Transactions on Instrumentation and Measurement. 71:1-16