Active learning approach to detecting standing dead trees from ALS point clouds combined with aerial infrared imagery. - Przemyslaw Polewski; Wei Yao 008; Marco Heurich; Peter Krzystek; Uwe Stilla (CVPR Workshops, 2015)

Combining Active and Semisupervised Learning of Remote Sensing Data Within a Renyi Entropy Regularization Framework. - Przemyslaw Polewski; Wei Yao 008; Marco Heurich; Peter Krzystek; Uwe Stilla (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2016)

Mapping Individual Tree Species and Vitality along Urban Road Corridors with LiDAR and Imaging Sensors: Point Density versus View Perspective. - Jianwei Wu; Wei Yao 008; Przemyslaw Polewski (Remote. Sens., 2018)

U-net for learning and inference of dense representation of multiple air pollutants from satellite imagery. - Jacquelyn Shelton; Przemyslaw Polewski; Wei Yao 008 (CI, 2020)

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 008; Marco Heurich (CoRR, 2021)

In the Danger Zone: U-Net Driven Quantile Regression can Predict High-risk SARS-CoV-2 Regions via Pollutant Particulate Matter and Satellite Imagery. - Jacquelyn Shelton; Przemyslaw Polewski; Wei Yao 008 (CoRR, 2021)

A hybrid convolutional neural network/active contour approach to segmenting dead trees in aerial imagery. - Jacquelyn A. Shelton; Przemyslaw Polewski; Wei Yao 008; Marco Heurich (CoRR, 2021)

Segmenting objects with Bayesian fusion of active contour models and convnet priors. - Przemyslaw Polewski; Jacquelyn Shelton; Wei Yao 008; Marco Heurich (CoRR, 2024)