Aquaculture and fisheries sectors are finding ingenious ways to grow and meet the soaring
human demand for nutrient-rich fish and seafood by efficiently utilizing the vast water …

Among the background of developments in automation and intelligence, machine learning
technology has been extensively applied in aquaculture in recent years, providing a new …

Intelligence technologies play an important role in increasing product quality and production
efficiency in digital aquaculture. Automatic fish detection will contribute to achieving …

The rapid emergence of deep learning (DL) technology has resulted in its successful use in
various fields, including aquaculture. DL creates both new opportunities and a series of …

Fish species identification is vital for aquaculture and fishery industries, stock management
of water bodies and environmental monitoring of aquatics. Traditional fish species …

The recent advancement in data science coupled with the revolution in digital and satellite
technology has improved the potential for artificial intelligence (AI) applications in the …

Development of computer vision algorithms using convolutional neural networks and deep
learning has necessitated ever greater amounts of annotated and labelled data to produce …

In recent years, there has been an enormous interest in using deep learning to classify
underwater images to identify various objects, such as fishes, plankton, coral reefs …

The ocean is an important ecosystem, and aquatic animals play an important role in the
biological world, especially in aquaculture. How to accurately and intelligently recognise …

Abstract Machine learning covers a large set of algorithms that can be trained to identify
patterns in data. Thanks to the increase in the amount of data and computing power …