DEEP LEARNING-BASED TRACKING OF MULTIPLE OBJECTS IN THE CONTEXT OF FARM ANIMAL ETHOLOGY

Ali, R.; Dorozynski, M.; Stracke, J.; Mehltretter, M.

doi:https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-509-2022

Articles | Volume XLIII-B2-2022

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Articles | Volume XLIII-B2-2022

https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-509-2022

Articles | Volume XLIII-B2-2022

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30 May 2022

| 30 May 2022

DEEP LEARNING-BASED TRACKING OF MULTIPLE OBJECTS IN THE CONTEXT OF FARM ANIMAL ETHOLOGY

R. Ali, M. Dorozynski, J. Stracke, and M. Mehltretter

R. Ali

Institute of Photogrammetry and GeoInformation, Leibniz University Hannover, Germany

M. Dorozynski

https://orcid.org/0000-0002-1293-6039

Institute of Photogrammetry and GeoInformation, Leibniz University Hannover, Germany

J. Stracke

Institute of Animal Science, University of Bonn, Germany

M. Mehltretter

Institute of Photogrammetry and GeoInformation, Leibniz University Hannover, Germany

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Integrating Viewing Direction and Image Features for Robust Multi-View Multi-Object 3D Pedestrian Tracking

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NoMeFormer: Non-Manifold Mesh Transformer

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Image-based Deep Learning for the time-dependent prediction of fresh concrete properties

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Depth-Aware Panoptic Segmentation

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DEEP LEARNING-BASED TRACKING OF MULTIPLE OBJECTS IN THE CONTEXT OF FARM ANIMAL ETHOLOGY

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