Lilja, A.[Adam]
* 2023: Zenseact Open Dataset: A large-scale and diverse multimodal dataset for autonomous driving
Lilja, K.K.
* 2017: use of advanced imaging technology in welfare technology solutions: Some ethical aspects, The
Lilja, M.
* 2006: Model-Based Segmentation of Reconstructed Dental X-Ray Volumes
* 2008: Methods of Artificial Enlargement of the Training Set for Statistical Shape Models
Liljeblad, B.[Bengt]
* 2019: Challenges and Best Practices for Deriving Temperature Data from an Uncalibrated UAV Thermal Infrared Camera
Liljedahl, A.
* 2014: Recursive active contours for hierarchical segmentation of wetlands in high-resolution satellite imagery of Arctic landscapes
* 2024: Segment Anything Model Can Not Segment Anything: Assessing AI Foundation Model's Generalizability in Permafrost Mapping
Includes: Liljedahl, A. Liljedahl, A.[Anna]
Liljedahl, A.K.[Anna K.]
* 2018: Deep Convolutional Neural Networks for Automated Characterization of Arctic Ice-Wedge Polygons in Very High Spatial Resolution Aerial Imagery
* 2018: Regional Patterns and Asynchronous Onset of Ice-Wedge Degradation since the Mid-20th Century in Arctic Alaska
* 2020: Transferability of the Deep Learning Mask R-CNN Model for Automated Mapping of Ice-Wedge Polygons in High-Resolution Satellite and UAV Images
* 2020: Understanding the synergies of deep learning and data fusion of multispectral and panchromatic high resolution commercial satellite imagery for automated ice-wedge polygon detection
* 2021: Object-Based Approach for Mapping Tundra Ice-Wedge Polygon Troughs from Very High Spatial Resolution Optical Satellite Imagery, An
* 2022: Automated Detection of Retrogressive Thaw Slumps in the High Arctic Using High-Resolution Satellite Imagery
* 2022: Convolutional Neural Networks for Automated Built Infrastructure Detection in the Arctic Using Sub-Meter Spatial Resolution Satellite Imagery
7 for Liljedahl, A.K.
Liljenstrom, H.
* 1998: Fingerprint Sub-Classification and Singular Point Detection
Liljeroth, M.
* 2016: PET Reconstruction With an Anatomical MRI Prior Using Parallel Level Sets