The use of machine learning (ML) in acoustics has received much attention in the last
decade. ML is unique in that it can be applied to all areas of acoustics. ML has …

Classification of zooplankton to species with broadband echosounder data could increase
the taxonomic resolution of acoustic surveys and reduce the dependence on net and trawl …

Abstract The mesopelagic zone (200–1000 m depth) contains high fish species diversity but
biomass and abundances are uncertain yet essential to understand ecosystem functioning …

Identifying sound-scattering organisms is a perennial challenge in fisheries acoustics. Most
practitioners classify backscatter based on direct sampling, frequency-difference thresholds …

Deep scattering layers (DSLs) play an important role in pelagic food webs, and are
inhabited by the world's most abundant invertebrates. Recent research has begun to reveal …

This study reviews current artificial intelligence (AI) systems legislation, the AI techniques
definition proposed by the AI Act and main applications of AI methods in the fisheries sector …

In this article, we propose an active target detector by using a shallow neural network (NN)
with novel features under small sonar data, where deep learning (DL) models are restricted …

Throughout all oceans, aggregations of zooplankton and ichthyoplankton appear as
horizontal sound scattering layers (SSLs) when detected with active acoustic techniques …

The impact of a cyclonic (C), an anticyclonic (AC) eddy and transition zone (TZ), which is the
area between the two eddies, on acoustic groups representing various mesopelagic …

Abstract The Northwest Pacific Ocean is one of the most productive fisheries in the world,
with small pelagic fish constituting a substantial portion of its fishery resources. Changes in …