Object Detection and Terrain Classification in Agricultural Fields Using 3D Lidar Data. - Mikkel Kragh Hansen; Rasmus N. Jørgensen; Henrik Pedersen (ICVS, 2015)

Automatic behaviour analysis system for honeybees using computer vision. - Gang Jun Tu; Mikkel Kragh Hansen; Per Kryger; Peter Ahrendt (Comput. Electron. Agric., 2016)

Towards a DSL for Perception-Based Safety Systems. - Johann Thor Mogensen Ingibergsson; Stefan-Daniel Suvei; Mikkel Kragh Hansen; Peter Christiansen; Ulrik Pagh Schultz (CoRR, 2016)

Multi-Modal Obstacle Detection in Unstructured Environments with Conditional Random Fields. - Mikkel Kragh Hansen; James Patrick Underwood (CoRR, 2017)

FieldSAFE: Dataset for Obstacle Detection in Agriculture. - Mikkel Kragh Hansen; Peter Christiansen; Morten Stigaard Laursen; Morten Larsen; Kim Arild Steen; Ole Green; Henrik Karstoft; Rasmus Nyholm Jørgensen (Sensors, 2017)

Towards Inverse Sensor Mapping in Agriculture. - Timo Korthals; Mikkel Kragh Hansen; Peter Christiansen; Ulrich Rückert 001 (CoRR, 2018)

Multi-Modal Detection and Mapping of Static and Dynamic Obstacles in Agriculture for Process Evaluation. - Timo Korthals; Mikkel Kragh Hansen; Peter Christiansen; Henrik Karstoft; Rasmus N. Jørgensen; Ulrich Rückert 001 (Frontiers Robotics AI, 2018)

Sparse-to-Dense Depth Completion in Precision Farming. - Sadaf Farkhani; Mikkel Fly Kragh; Peter Hviid Christiansen; Rasmus Nyholm Jørgensen; Henrik Karstoft (ICVISP, 2019)

Automatic grading of human blastocysts from time-lapse imaging. - Mikkel Fly Kragh; Jens Rimestad; Jørgen Berntsen; Henrik Karstoft (Comput. Biol. Medicine, 2019)

UnsuperPoint: End-to-end Unsupervised Interest Point Detector and Descriptor. - Peter Hviid Christiansen; Mikkel Fly Kragh; Yury Brodskiy; Henrik Karstoft (CoRR, 2019)

Multimodal obstacle detection in unstructured environments with conditional random fields. - Mikkel Kragh Hansen; James Patrick Underwood (J. Field Robotics, 2020)

Robust and generalizable embryo selection based on artificial intelligence and time-lapse image sequences. - Jørgen Berntsen; Jens Rimestad; Jacob Theilgaard Lassen; Dang Tran; Mikkel Fly Kragh (CoRR, 2021)

Development and validation of deep learning based embryo selection across multiple days of transfer. - Jacob Theilgaard Lassen; Mikkel Fly Kragh; Jens Rimestad; Martin Nygård Johansen; Jørgen Berntsen (CoRR, 2022)

Predicting Embryo Viability Based on Self-Supervised Alignment of Time-Lapse Videos. - Mikkel Fly Kragh; Jens Rimestad; Jacob Theilgaard Lassen; Jørgen Berntsen; Henrik Karstoft (IEEE Trans. Medical Imaging, 2022)