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 …

The task of quantification consists in providing an aggregate estimation (eg, the class
distribution in a classification problem) for unseen test sets, applying a model that is trained …

Plankton are the most fundamental components of ocean ecosystems, due to their function
at many levels of the oceans food chain. Studying and monitoring plankton distribution is …

The large data sets provided by in situ optical microscopes are allowing us to answer
longstanding questions about the dynamics of planktonic ecosystems. To deal with the influx …

Advances in both hardware and software are enabling rapid proliferation of in situ plankton
imaging methods, requiring more effective machine learning approaches to image …

In this paper, we present a study about an automated system for monitoring underwater
ecosystems. The system here proposed is based on the fusion of different deep learning …

The study of marine plankton data is vital to monitor the health of the world's oceans. In
recent decades, automatic plankton recognition systems have proved useful to address the …

Accurate and detailed reporting of methods is essential for scientific progress, yet it is widely
accepted that authors across all scientific fields tend to provide insufficient methods detail …

In this work, we present MorphoCluster, a software tool for data-driven, fast, and accurate
annotation of large image data sets. While already having surpassed the annotation rate of …

This article reports the development of an underwater imaging system and its trial on a
moored surface buoy for in situ plankton monitoring of coastal waters. The imager features …