Search Results for author:
Found 17 papers, 8 papers with code
Gravity-Informed Deep Learning Framework for Predicting Ship Traffic Flow and Invasion Risk of Non-Indigenous Species via Ballast Water Discharge
Along these lines, this research contributes to a better understanding of invasive species risk assessment.
Improving Dribbling, Passing, and Marking Actions in Soccer Simulation 2D Games Using Machine Learning
The RoboCup 2D Soccer Simulation League is a stochastic, partially observable soccer environment in which 24 autonomous agents play on two opposing teams.
Probabilistic Feature Augmentation for AIS-Based Multi-Path Long-Term Vessel Trajectory Forecasting
This study explores using AIS data to prevent vessel-to-whale collisions by forecasting long-term vessel trajectories from engineered AIS data sequences.
Denoising Opponents Position in Partial Observation Environment
Our idea is to predict opponent positions while they have yet to be seen in a finite number of cycles using machine learning methods to make more accurate actions such as pass.
Pyrus Base: An Open Source Python Framework for the RoboCup 2D Soccer Simulation
To conquer the challenges of C++ base codes and provide a powerful baseline for developing machine learning concepts, we introduce Pyrus, the first Python base code for SS2D.
A semi-supervised methodology for fishing activity detection using the geometry behind the trajectory of multiple vessels
To this end, we leverage the unsupervised nature of cluster analysis to label the trajectory geometry highlighting the changes in the vessel's moving pattern which tends to indicate fishing activity.
CYRUS Soccer Simulation 2D Team Description Paper 2022
Soccer Simulation 2D League is one of the major leagues of RoboCup competitions.
Unfolding AIS transmission behavior for vessel movement modeling on noisy data leveraging machine learning
The oceans are a source of an impressive mixture of complex data that could be used to uncover relationships yet to be discovered.
Survey of Generative Methods for Social Media Analysis
This survey draws a broad-stroke, panoramic picture of the State of the Art (SoTA) of the research in generative methods for the analysis of social media data.
PTRAIL - A python package for parallel trajectory data preprocessing
Trajectory data represent a trace of an object that changes its position in space over time.
PTRAIL -- A python package for parallel trajectory data preprocessing
Trajectory data represent a trace of an object that changes its position in space over time.
Continuous Control with Deep Reinforcement Learning for Autonomous Vessels
We designed our model based on Deep Deterministic Policy Gradient, local view maker, and planner.
Analyzing the Impact of Foursquare and Streetlight Data with Human Demographics on Future Crime Prediction
Finding the factors contributing to criminal activities and their consequences is essential to improve quantitative crime research.
Challenges in Vessel Behavior and Anomaly Detection: From Classical Machine Learning to Deep Learning
The global expansion of maritime activities and the development of the Automatic Identification System (AIS) have driven the advances in maritime monitoring systems in the last decade.
Using Deep Reinforcement Learning Methods for Autonomous Vessels in 2D Environments
Experimental results show that the proposed method enhanced the performance of VVN by 55. 31 on average for long-distance missions.
Wise Sliding Window Segmentation: A classification-aided approach for trajectory segmentation
One of the most critical steps for trajectory data mining is segmentation.
Unsupervised Behavior Change Detection in Multidimensional Data Streams for Maritime Traffic Monitoring
The worldwide growth of maritime traffic and the development of the Automatic Identification System (AIS) has led to advances in monitoring systems for preventing vessel accidents and detecting illegal activities.
