Package ais provides types and methods for conducting data science on signals generated by maritime entities radiating from an Automated Identification System (AIS) transponder as mandated by the International Maritime Organization (IMO) for vessels over 300 gross tons and all passenger vessels.
Open AI Gymnassium Compatible RL environment for Maritime Navigation
Cartographic Sounding Selection for ENCs
Project on AIS data analysis to extract valuable maritime insights and improve vessel monitoring and navigation
Imbalanced data problem image/maritime flags detection. Balancing by using SMOTE, ADASYN, Augmentation, Autoencoder and DGAN. Detection by using two-stage dectetors like: R-CNN, Faster R-CNN and Mask R-CNN.
NMEA 2000 (n2k) for Humans and Agents
An 88.54% accurate CNN-based solution for Airbus Ship Detection Challenge that carries out maritime monitoring to prevent illegal activities and accidents at sea through satellite imagery analysis.
Implementation of augmentation, SMOTE, ADASYN, AE, DGAN for oversampling image data used in detection (YOLO and others one stage detectors). Maritime flags/code scenario.
Deep Quantile Regression Synthetic Aperture Radar Ship Size
Practicality of Green H2 Economy for Industry and Maritime Sector Decarbonization through Multi-objective Optimization and RNN-LSTM Model Analysis
USV Mission control for automated vessel operations docking and navigation
World Models for Maritime Mobility
Exploring potential confounding effects on US maritime trade from 2010-2020
d3.js visualization representing the container carrier alliances serving the Massachusetts Port Authority (MassPort) for FY 2014 - FY 2020
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