Semantic Segmentation for Fully Automated Macrofouling Analysis on Coatings after Field Exposure

Biofouling is a major challenge for sustainable shipping, filter membranes, heat exchangers, and medical devices. The development of fouling-resistant coatings requires the evaluation of their effectiveness. Such an evaluation is usually based on the assessment of fouling progression after different exposure times to the target medium (e.g., salt water). The manual assessment of macrofouling requires expert knowledge about local fouling communities due to high variances in phenotypical appearance, has single-image sampling inaccuracies for certain species, and lacks spatial information. Here we present an approach for automatic image-based macrofouling analysis. We created a dataset with dense labels prepared from field panel images and propose a convolutional network (adapted U-Net) for the semantic segmentation of different macrofouling classes. The establishment of macrofouling localization allows for the generation of a successional model which enables the determination of direct surface attachment and in-depth epibiotic studies.Comment: 33 pages, 10 figure

Machine learning techniques to characterize functional traits of plankton from image data

Plankton imaging systems supported by automated classification and analysis have improved ecologists' ability to observe aquatic ecosystems. Today, we are on the cusp of reliably tracking plankton populations with a suite of lab-based and in situ tools, collecting imaging data at unprecedentedly fine spatial and temporal scales. But these data have potential well beyond examining the abundances of different taxa; the individual images themselves contain a wealth of information on functional traits. Here, we outline traits that could be measured from image data, suggest machine learning and computer vision approaches to extract functional trait information from the images, and discuss promising avenues for novel studies. The approaches we discuss are data agnostic and are broadly applicable to imagery of other aquatic or terrestrial organisms

Morphometrics of Southern Ocean diatoms using high throughput imaging and semi-automated image analysis

Since the ADIAC project, which ended more than 15 years ago, not much progress in automating morphometric analysis of diatoms from slide-mounted material has been published, and no ready-to-use system has become available. This thesis work is the first to implement such a system completely, covering all aspects of the underlying imaging and image processing pipeline, by combining a commercially available slide scanning microscope with my diatom morphometry software SHERPA. I was able to show the applicability as well as the potential of this approach by executing a series of smaller and two large-scale morphometry projects. The extensive sampling sizes, which were made possible only by the new workflow, enabled the first observations of life cycle related size distribution changes of Fragilariopsis kerguelensis in its natural habitat, leading to hypotheses on influences of reproduction, grazing and environmental changes in one of the most important diatom species of the Southern Ocean. In a second large-scale investigation, SHERPA's precise morphometric measurements revealed a second F. kerguelensis morphotype, which has not been recognized before, even though the species, as well as the very material I analyzed, have been investigated intensely before by experienced diatomists; a result not disqualifying their work, but rather underlining that explicit and precise quantification of morphological information has a strong potential to generate novel scientific insights. This new morphotype has implications on the utilization of paleo-proxies which are based on geometrical valve features of F. kerguelensis. Differentiating both morphotypes might improve established methods and possibly provides a new proxy for summer sea surface temperature

Flow-3D CFD model of bifurcated open channel flow: setup and validation

Bifurcation is a morphological feature present in most of fluvial systems; where a river splits into two channels, each bearing a portion of the flow and sediments. Extensive theoretical studies of river bifurcations were performed to understand the nature of flow patterns at such diversions. Nevertheless, the complexity of the flow structure in the bifurcated channel has resulted in various constraints on physical experimentation, so computational modelling is required to investigate the phenomenon. The advantages of computational modelling compared with experimental research (e.g. simple variable control, reduced cost, optimize design condition etc.) are widely known. The great advancement of computer technologies and the exponential increase in power, memory storage and affordability of high-speed machines in the early 20th century led to evolution and wide application of numerical fluid flow simulations, generally referred to as Computational Fluid Dynamics {CFD). In this study, the open-channel flume with a lateral channel established by Momplot et al (2017) is modelled in Flow-3D. The original investigation on divided flow of equal widths as simulated in ANSYS Fluent and validated with velocity measurements