Drone and ground-truth data collection, image annotation and machine learning: A protocol for coastal habitat mapping and classification.

Aerial drone imaging is an efficient tool for mapping and monitoring of coastal habitats at high spatial and temporal resolution. Specifically, drone imaging allows for time- and cost-efficient mapping covering larger areas than traditional mapping and monitoring techniques, while also providing more detailed information than those from airplanes and satellites, enabling for example to differentiate various types of coastal vegetation. Here, we present a systematic method for shallow water habitat classification based on drone imagery.

Polymer Surface Dissection for Correlated Microscopic and Compositional Analysis of Bacterial Aggregates during Membrane Biofouling.

Multispecies biofilms are a common limitation in membrane bioreactors, causing membrane clogging, degradation, and failure. There is a poor understanding of biological fouling mechanisms in these systems due to the limited number of experimental techniques useful for probing microbial interactions at the membrane interface. Here, we develop a new experimental method, termed polymer surface dissection (PSD), to investigate multispecies assembly processes over membrane surfaces.

Explaining decisions of deep neural networks used for fish age prediction.

Age-reading of fish otoliths (ear stones) is important for the sustainable management of fish resources. However, the procedure is challenging and requires experienced readers to carefully examine annual growth zones. In a recent study, convolutional neural networks (CNNs) have been demonstrated to perform reasonably well on automatically predicting fish age from otolith images.