The detection of clouds is one of the first steps in the pre-processing of remotely sensed
data. At coarse spatial resolution (> 100 m), clouds are bright and generally distinguishable …

Two-stage object detectors generate object proposals and classify them to detect objects in
images. These proposals often do not perfectly contain the objects but overlap with them in …

Wildlife surveys are key to assessing the health of global biodiversity. Traditional field and
aerial methods however have significant limitations, including high costs, substantial time …

Abstract Lightweight Unmanned Aerial Vehicles (UAVs) are emerging as a remote sensing
survey tool for animal monitoring in several fields, such as precision livestock farming …

Incorporating pixel contextual information is critical for accurate segmentation. In this paper,
we show that an effective way to incorporate contextual information is through a patch-based …

Using 51 orthomosaics of 11 breeding locations of the Antarctic shag (Leucocarbo
bransfieldensis), we propose a method for automating counting of shag nests. This is …

Semi-supervised semantic segmentation methods leverage unlabeled data by pseudo-
labeling them. Thus the success of these methods hinges on the reliability of the pseudo …

As the largest species of birds in Antarctica, penguins are called “biological indicators”.
Changes in the environment will cause population fluctuations. Therefore, developing a …

Satellite-based remote sensing and uncrewed aerial imagery play increasingly important
roles in the mapping of wildlife populations and wildlife habitat, but the availability of …

In the context of the current nature crisis, being able to reliably and cost‐effectively track
subtle changes in the biosphere across adequate spatial and temporal extents and …