TreeLearn: A Comprehensive Deep Learning Method for Segmenting Individual Trees from Forest Point Clouds. - Jonathan Henrich; Jan van Delden; Dominik Seidel; Thomas Kneib; Alexander S. Ecker (CoRR, 2023)

Entwicklung eines vielfältigen und anspruchsvollen Benchmark-Datensatzes für die Detektion von Schweinen in Bildern. - Jonathan Henrich; Christian Post; Thomas Kneib; Ramin Yahyapour; Sven Bingert; Imke Traulsen (GIL, 2024)

Computer Vision for Primate Behavior Analysis in the Wild. - Richard Vogg; Timo Lüddecke; Jonathan Henrich; Sharmita Dey; Matthias Nuske; Valentin Hassler; Derek Murphy; Julia Fischer; Julia Ostner; Oliver Schülke; Peter M. Kappeler; Claudia Fichtel; et al. (CoRR, 2024)

Towards general deep-learning-based tree instance segmentation models. - Jonathan Henrich; Jan van Delden (CoRR, 2024)

TreeLearn: A deep learning method for segmenting individual trees from ground-based LiDAR forest point clouds. - Jonathan Henrich; Jan van Delden; Dominik Seidel; Thomas Kneib; Alexander S. Ecker (Ecol. Informatics, 2024)

Benchmarking pig detection and tracking under diverse and challenging conditions. - Jonathan Henrich; Christian Post; Maximilian Zilke; Parth Shiroya; Emma Chanut; Amir Mollazadeh Yamchi; Ramin Yahyapour; Thomas Kneib; Imke Traulsen (CoRR, 2025)