The precise estimation of the number of trees, their individual tree locations, along with
species information, is crucial for enhancing ecosystem services in urban areas. Previous …

Dynamic imaging is a beneficial tool for interventions to assess physiological changes.
Nonetheless during dynamic MRI, while achieving a high temporal resolution, the spatial …

The IARAI Traffic4cast competitions at NeurIPS 2019 and 2020 showed that neural networks
can successfully predict future traffic conditions 1 hour into the future on simply aggregated …

Species identification is one of the key steps in the management and conservation planning
of many forest ecosystems. We introduce Deep BarkID, a portable tree identification system …

As remote sensing transforms forest and urban tree management, automating tree species
classification is now a major challenge to harness these advances for forestry and urban …

Efficient tree species identification is of great importance in forest inventory and
management. As the textural properties of tree barks vary less notably as a result of …

Plant recognition is a challenging task due to the following elements: many classes, the
variability of organs within a species, the similarity of organs between species, the shooting …

Novel ground-based remote sensing approaches have demonstrated high potential for
accurate and detailed mapping and monitoring of forest ecosystems. These methods enable …

This paper presents the SARSNet architecture, developed to address the growing
challenges in Synthetic Aperture Radar (SAR) deep learning-based automatic water body …

The task of tree species classification through deep learning has been challenging for the
forestry community, and the lack of standardized datasets has hindered further progress. Our …