Rapid population growth creating an excessive pressure on the marine environment and
thus monitoring of marine ecosystem is essential. However, due to high technical and …

Zooplankton analysis represents a bottleneck in marine ecology studies due to the difficulty
to obtain zooplankton data. The last decades have seen the intense development of …

The purpose of this research study is determining that artificial intelligence applications
related to the fish classification also that taxonomy. Research describes that aquatic …

Selecting the optimal spatiotemporal scale in fishing ground prediction models can
maximize prediction accuracy. Current research on spatiotemporal scales shows that they …

Abstract Marine Ecosystem Models (MEMs) are increasingly driven by Earth System Models
(ESMs) to better understand marine ecosystem dynamics, and to analyze the effects of …

Among the various challenges facing tropical tuna purse seine fleet are the need to reduce
fuel consumption and carbon footprint, as well as minimising bycatch of vulnerable species …

Aquatic biodiversity monitoring relies on species recognition from images. While deep
learning (DL) streamlines the recognition process, the performance of these method is …

Most coral reef studies focus on scleractinian (stony) corals to indicate reef condition, but
there are other prominent assemblages that play a role in ecosystem structure and function …

Zooplankton play a crucial role in the ocean's ecology, as they form a foundational
component in the food chain by consuming phytoplankton or other zooplankton, supporting …

Automating identification of benthic habitats from imagery, with Machine Learning (ML), is
necessary to contribute efficiently and effectively to marine spatial planning. A promising …