Maritime Traffic Monitoring Based on Vessel Detection, Tracking, State Estimation, and Trajectory Prediction
By L. Perera, Paulo Jorge Ramalho Oliveira, Carlos Soares. IEEE transactions on intelligent transportation systems (Print), 2012
337 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Ocean Engineering
View Paper: https://www.semanticscholar.org/paper/4de4a2df489ef901eba9ed7ea0b5c65fe5d91e5e
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Ning Wang
- Jing-Chao Sun
- Yancheng Liu
- Shuaian Wang
- Kevin X. Li
- Chunjiang Qian
- H. Jia
- Dong Yang
Citations in the corpus
- How big data enriches maritime research – a critical review of Automatic Identification System (AIS) data applications (2019, background): “Perera et al. (2012) developed a maritime traffic monitoring system based on vessel detection, tracking, state estimation, and trajectory prediction.”
- Adaptive Robust Finite-Time Trajectory Tracking Control of Fully Actuated Marine Surface Vehicles (2016, background): “In this respect, tracking of an MSV to a desired trajectory has become a crucial issue in both marine engineering [2] and control community [3].”
- Ship Collision Avoidance and COLREGS Compliance Using Simulation-Based Control Behavior Selection With Predictive Hazard Assessment (2016, neutral): “In this paper, we address the design of the collision avoidance control algorithm, that must decide on the control actions required to ensure compliance with COLREGS and minimize hazard to an acceptable level based on the available sensor information.”