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Oceans and Seas

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Using a stacked-autoencoder neural network model to estimate sea state bias for a radar altimeter.

PloS one
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...

MAIA-A machine learning assisted image annotation method for environmental monitoring and exploration.

PloS one
Digital imaging has become one of the most important techniques in environmental monitoring and exploration. In the case of the marine environment, mobile platforms such as autonomous underwater vehicles (AUVs) are now equipped with high-resolution c...

High-resolution acoustic surveys with diving gliders come at a cost of aliasing moving targets.

PloS one
Underwater gliders are autonomous robots that follow a slow, see-saw path and may be deployed for months on end. Gliders have a dramatically lower payload capacity than research vessels and are thus limited to more simple instrumentation. They have t...

Automatic method to monitor floating macroalgae blooms based on multilayer perceptron: case study of Yellow Sea using GOCI images.

Optics express
Timely and accurate information about floating macroalgae blooms (MAB), including their distribution, movement, and duration, is crucial in order for local government and residents to grasp the whole picture, and then plan effectively to restrain eco...

Identifying floating plastic marine debris using a deep learning approach.

Environmental science and pollution research international
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...

Deep learning classification for improved bicoherence feature based on cyclic modulation and cross-correlation.

The Journal of the Acoustical Society of America
This paper aims to present an improved bicoherence spectrum (IBS) combined with cyclic modulation spectrum (CMS) and cross-correlation that is suitable for classification of hydrophone signals involving deep learning (DL). First, the proposed feature...

High-resolution bathymetry by deep-learning-based image superresolution.

PloS one
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...

Beluga whale acoustic signal classification using deep learning neural network models.

The Journal of the Acoustical Society of America
Over a decade after the Cook Inlet beluga (Delphinapterus leucas) was listed as endangered in 2008, the population has shown no sign of recovery. Lack of ecological knowledge limits the understanding of, and ability to manage, potential threats imped...

An intelligent way for discerning plastics at the shorelines and the seas.

Environmental science and pollution research international
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...

Mobile robotic platforms for the acoustic tracking of deep-sea demersal fishery resources.

Science robotics
Knowing the displacement capacity and mobility patterns of industrially exploited (i.e., fished) marine resources is key to establishing effective conservation management strategies in human-impacted marine ecosystems. Acquiring accurate behavioral i...