5 papers
Learning Image-based Tree Crown Segmentation from Enhanced Lidar-based Pseudo-labels
Julius Pesonen, Stefan Rua, Josef Taher +3
Mapping individual tree crowns is essential for tasks such as maintaining urban tree inventories and monitoring forest health, which help us understand and care for our environment…
Distant Object Localisation from Noisy Image Segmentation Sequences
Julius Pesonen, Arno Solin, Eija Honkavaara
3D object localisation based on a sequence of camera measurements is essential for safety-critical surveillance tasks, such as drone-based wildfire monitoring. Localisation of obje…
Road Grip Uncertainty Estimation Through Surface State Segmentation
Jyri Maanpää, Julius Pesonen, Iaroslav Melekhov +2
Slippery road conditions pose significant challenges for autonomous driving. Beyond predicting road grip, it is crucial to estimate its uncertainty reliably to ensure safe vehicle…
Detecting Wildfires on UAVs with Real-time Segmentation Trained by Larger Teacher Models
Julius Pesonen, Teemu Hakala, Väinö Karjalainen +6
Early detection of wildfires is essential to prevent large-scale fires resulting in extensive environmental, structural, and societal damage. Uncrewed aerial vehicles (UAVs) can co…
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…