Marine pollution presents a pressing environmental issue in the oceanic realm. To examine
the identification, detection, and mitigation technologies employed for marine pollution, a …

Marine scientists use a variety of collection and monitoring methods to survey macrolitter in
aquatic environments, aiming to assess the level of pollution and design mitigation actions …

Recent advances in remote sensing hyperspectral imaging and artificial intelligence (AI)
bring exciting opportunities to various fields of science and industry that can directly benefit …

The increase in the global demand for plastics, and more recently during the pandemic, is a
major concern for the future of plastic waste pollution and microplastics. Efficient microplastic …

Recently, deep learning algorithms, specifically convolutional neural networks (CNNs), have
played an important role in remote sensing image classification, including wetland mapping …

The persistent plastic litter, originating from different sources and transported from rivers to
oceans, has posed serious biological, ecological, and chemical effects on the marine …

Marine plastic pollution is an emerging environmental problem since it pollutes the ocean,
air and food whilst endangering the ocean wildlife via the ingestion and entanglements …

The emergence of deep learning techniques has revolutionized the use of machine learning
algorithms to classify complicated environments, notably in remote sensing. Convolutional …

Despite the significant negative impact of marine pollution on the ecosystem and humans, its
automated detection and tracking from the broadly available satellite data is still a major …

Deep learning, a data-driven technology, has attracted widespread attention from various
disciplines due to the rapid advancements in the Internet of Things (IoT) big data, machine …