17 citations · 26 across the 5 of their papers we have counts for
5 papers
Multispectral airborne laser scanning for tree species classification: a benchmark of machine learning and deep learning algorithms
Josef Taher, Eric Hyyppä, Matti Hyyppä +46
Climate-smart and biodiversity-preserving forestry demands precise information on forest resources, extending to the individual tree level. Multispectral airborne laser scanning (A…
Dense Road Surface Grip Map Prediction from Multimodal Image Data
Jyri Maanpää, Julius Pesonen, Heikki Hyyti +5
Slippery road weather conditions are prevalent in many regions and cause a regular risk for traffic. Still, there has been less research on how autonomous vehicles could detect sli…
Towards High-Definition Maps: a Framework Leveraging Semantic Segmentation to Improve NDT Map Compression and Descriptivity
Petri Manninen, Heikki Hyyti, Ville Kyrki +3
High-Definition (HD) maps are needed for robust navigation of autonomous vehicles, limited by the on-board storage capacity. To solve this, we propose a novel framework, Environmen…
Leveraging Road Area Semantic Segmentation with Auxiliary Steering Task
Jyri Maanpää, Iaroslav Melekhov, Josef Taher +2
Robustness of different pattern recognition methods is one of the key challenges in autonomous driving, especially when driving in the high variety of road environments and weather…
Multimodal End-to-End Learning for Autonomous Steering in Adverse Road and Weather Conditions
Jyri Maanpää, Josef Taher, Petri Manninen +3
Autonomous driving is challenging in adverse road and weather conditions in which there might not be lane lines, the road might be covered in snow and the visibility might be poor.…