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The small sizes of most marine plankton necessitate that plankton sampling occur on fine spatial scales, yet our questions often span large spatial areas. Underwater imaging can provide a solution to this sampling conundrum but collects large quantities of data that require an automated approach to image analysis. Machine learning for plankton classification, and high-performance computing (HPC) infrastructure, are critical to...
Content-Aware Segmentation of Objects Spanning a Large Size Range: Application to Plankton ImagesOA Marine
As the basis of oceanic food webs and a key component of the biological carbon pump, planktonic organisms play major roles in the oceans. Their study benefited from the development of in situ imaging instruments, which provide higher spatio-temporal resolution than previous tools. But these instruments collect huge quantities of images, the vast majority of which are of marine snow particles or imaging artifacts. Among them, t...
In our 2011 synthesis (Bowman et al ., Journal of Biogeography , 2011, 38 , 2223–2236), we argued for a holistic approach to human issues in fire science that we term ‘pyrogeography’. Coughlan & Petty ( Journal of Biogeography , 2013, 40 , 1010–1012) critiqued our paper on the grounds that our ‘pyric phase’ model was built on outdated views of cultural development, claiming we developed it to be the unifying explanatory framew...
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