AI Medical Compendium Journal:
Marine pollution bulletin

Showing 41 to 50 of 64 articles

Analysis and forecasting of national marine litter based on coastal data in South Korea from 2009 to 2021.

Marine pollution bulletin
In this study, statistical analysis and forecasting were performed using coastal litter data of Korea. The analysis indicated that rope and vinyl accounted for the highest proportion of coastal litter items. The statistical analysis of the national c...

Detection of marine oil-like features in Sentinel-1 SAR images by supplementary use of deep learning and empirical methods: Performance assessment for the Great Barrier Reef marine park.

Marine pollution bulletin
Continuous monitoring of oil discharges in coastal and open ocean waters using Earth Observation (EO) has undeniably contributed to diminishing their occurrence wherever a detection system was in place, such as in Europe (EMSA's CleanSeaNet) or in th...

Ocean oil spill detection from SAR images based on multi-channel deep learning semantic segmentation.

Marine pollution bulletin
One of the major threats to marine ecosystems is pollution, particularly, that associated with the offshore oil and gas industry. Oil spills occur in the world's oceans every day, either as large-scale spews from drilling-rig or tanker accidents, or ...

Automated Secchi disk depth measurement based on artificial intelligence object recognition.

Marine pollution bulletin
Water transparency affects the degree of sunlight penetration in water, which is important to many water quality processes. It can be visually measured by lowering a Secchi disk (SD) into water and recording its disappearance depth - the Secchi disk ...

Deploying deep learning to estimate the abundance of marine debris from video footage.

Marine pollution bulletin
The insatiable desire of society for plastic goods has led to synthetic materials becoming omnipresent in the marine environment. In attempting to address the problem of plastic pollution, we propose an image classifier based on the YOLOv5 deep learn...

Is the use of deep learning an appropriate means to locate debris in the ocean without harming aquatic wildlife?

Marine pollution bulletin
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...

Sunken oil detection and classification using MBES backscatter data.

Marine pollution bulletin
Sunken oil incidents have occurred multiple times in the Bohai Sea over the past ten years. Currently, quick and effective sunken oil detection and classification remains a difficult problem. In this study, sonar detection experiments are conducted t...

A novel deep learning method for marine oil spill detection from satellite synthetic aperture radar imagery.

Marine pollution bulletin
Oil spill discharges from operational maritime activities like ships, oil rigs and other structures, leaking pipelines, as well as natural hydrocarbon seepage pose serious threats to marine ecosystems and fisheries. Satellite synthetic aperture radar...

Pixel-level image classification for detecting beach litter using a deep learning approach.

Marine pollution bulletin
Mitigating and preventing beach litter from entering the ocean is urgently required. Monitoring beach litter solely through human effort is cumbersome, with respect to both time and cost. To address this problem, an artificial intelligence technique ...

Functionalization of remote sensing and on-site data for simulating surface water dissolved oxygen: Development of hybrid tree-based artificial intelligence models.

Marine pollution bulletin
Dissolved oxygen (DO) is an important indicator of river health for environmental engineers and ecological scientists to understand the state of river health. This study aims to evaluate the reliability of four feature selector algorithms i.e., Borut...