AIMC Topic: Oceans and Seas

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A Semi-Supervised Methodology for Fishing Activity Detection Using the Geometry behind the Trajectory of Multiple Vessels.

Sensors (Basel, Switzerland) Aug 13, 2022
Automatic Identification System (AIS) messages are useful for tracking vessel activity across oceans worldwide using radio links and satellite transceivers. Such data play a significant role in tracking vessel activity and mapping mobility patterns s...
Oceans and Seas Hunting Neural Networks, Computer Cluster Analysis
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Is the use of deep learning an appropriate means to locate debris in the ocean without harming aquatic wildlife?

Marine pollution bulletin Jul 1, 2022
With the global issue of marine debris ever expanding, it is imperative that the technology industry steps in. The aim is to find if deep learning can successfully distinguish between marine life and synthetic debris underwater. This study assesses w...
Deep Learning Oceans and Seas Ecosystem Animals, Wild Artificial Intelligence Animals
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Improvement of DBR routing protocol in underwater wireless sensor networks using fuzzy logic and bloom filter.

PloS one Feb 7, 2022
Routing protocols for underwater wireless sensor networks (UWSN) and underwater Internet of Things (IoT_UWSN) networks have expanded significantly. DBR routing protocol is one of the most critical routing protocols in UWSNs. In this routing protocol,...
Eutrophication Water Algorithms Computer Simulation Cluster Analysis Quality Improvement Biosensing Techniques Fuzzy Logic Humans Wireless Technology Oceans and Seas Electric Power Supplies Computer Communication Networks Filtration Water Microbiology
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Long-Term Ship Position Prediction Using Automatic Identification System (AIS) Data and End-to-End Deep Learning.

Sensors (Basel, Switzerland) Oct 28, 2021
The establishment of maritime safety and security is an important concern. Ship position prediction for maritime situational awareness (MSA), as a critical aspect of maritime safety and security, requires a longer time interval than collision avoidan...
Deep Learning Ships Oceans and Seas
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Autonomous Marine Robot Based on AI Recognition for Permanent Surveillance in Marine Protected Areas.

Sensors (Basel, Switzerland) Apr 10, 2021
The world's oceans are one of the most valuable sources of biodiversity and resources on the planet, although there are areas where the marine ecosystem is threatened by human activities. Marine protected areas (MPAs) are distinctive spaces protected...
Conservation of Natural Resources Oceans and Seas Biodiversity Humans Artificial Intelligence Ecosystem Robotics
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Soft Robots for Ocean Exploration and Offshore Operations: A Perspective.

Soft robotics Jan 15, 2021
The ocean and human activities related to the sea are under increasing pressure due to climate change, widespread pollution, and growth of the offshore energy sector. Data, in under-sampled regions of the ocean and in the offshore patches where the i...
Humans Technology Robotics Oceanography Climate Change Oceans and Seas
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An intelligent way for discerning plastics at the shorelines and the seas.

Environmental science and pollution research international Jul 25, 2020
Irrespective of how plastics litter the coastline or enter the sea, they pose a major threat to birds and marine life alike. In this study, an artificial intelligence tool was used to create an image classifier based on a convolutional neural network...
Waste Products Humans Oceans and Seas Environmental Monitoring Artificial Intelligence Plastics Animals
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High-resolution bathymetry by deep-learning-based image superresolution.

PloS one Jul 1, 2020
Seafloor mapping to create bathymetric charts of the oceans is important for various applications. However, making high-resolution bathymetric charts requires measuring underwater depths at many points in sea areas, and thus, is time-consuming and co...
Deep Learning Oceans and Seas Image Processing, Computer-Assisted Signal-To-Noise Ratio
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Identifying floating plastic marine debris using a deep learning approach.

Environmental science and pollution research international Apr 18, 2019
Estimating the volume of macro-plastics which dot the world's oceans is one of the most pressing environmental concerns of our time. Prevailing methods for determining the amount of floating plastic debris, usually conducted manually, are time demand...
Oceans and Seas Deep Learning Plastics Environmental Monitoring Waste Products
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Using a stacked-autoencoder neural network model to estimate sea state bias for a radar altimeter.

PloS one Dec 17, 2018
This paper constructed a stacked-autoencoder neural network model (SAE model) to estimate sea state bias (SSB) based on radar altimeter data. Six cycles of the geophysical data record (GDR) from Jason-1/2 radar altimeters were used as a training data...
Radar Environmental Monitoring Neural Networks, Computer Oceans and Seas Models, Statistical
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