activity
20212026
most citedA hybrid convolutional neural network/active contour approach to segmenting dead trees in aerial imagery

1 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.DL2026

3Dtrees.earth: community research infrastructure for tree and forest analysis using close-range LiDAR data

Janusch Vajna-Jehle, Kilian Gerberding, Daniel Lusk +275

From individual trees to forest stands, three-dimensional structure shapes carbon, water, and energy flows, habitat conditions, and resource availability. Yet tree and forest struc…

cs.CV2024

Bayesian Fusion of Active Contour Models and ConvNet Priors for Standing Dead Tree Segmentation

Przemyslaw Polewski, Jacquelyn Shelton, Wei Yao +1

Instance segmentation is a core computer vision task with great practical significance. Recent advances, driven by large-scale benchmark datasets, have yielded good general-purpose…

cs.CV2023★ 1 cited

Classification of Single Tree Decay Stages from Combined Airborne LiDAR Data and CIR Imagery

Tsz Chung Wong, Abubakar Sani-Mohammed, Jinhong Wang +3

Understanding forest health is of great importance for the conservation of the integrity of forest ecosystems. In this regard, evaluating the amount and quality of dead wood is of…

cs.CV2021★ 1 cited

A hybrid convolutional neural network/active contour approach to segmenting dead trees in aerial imagery

Jacquelyn A. Shelton, Przemyslaw Polewski, Wei Yao +1

The stability and ability of an ecosystem to withstand climate change is directly linked to its biodiversity. Dead trees are a key indicator of overall forest health, housing one-t…

cs.CV2021

Instance segmentation of fallen trees in aerial color infrared imagery using active multi-contour evolution with fully convolutional network-based intensity priors

Przemyslaw Polewski, Jacquelyn Shelton, Wei Yao +1

In this paper, we introduce a framework for segmenting instances of a common object class by multiple active contour evolution over semantic segmentation maps of images obtained th…