2 citations · 3 across the 7 of their papers we have counts for
6 papers · 1 filter
Event-Only Drone Trajectory Forecasting with RPM-Modulated Kalman Filtering
Hari Prasanth S. M., Pejman Habibiroudkenar, Eerik Alamikkotervo +2
Event cameras provide high-temporal-resolution visual sensing that is well suited for observing fast-moving aerial objects; however, their use for drone trajectory prediction remai…
Automatic Labelling for Low-Light Pedestrian Detection
Dimitrios Bouzoulas, Eerik Alamikkotervo, Risto Ojala
Pedestrian detection in RGB images is a key task in pedestrian safety, as the most common sensor in autonomous vehicles and advanced driver assistance systems is the RGB camera. Lo…
Label Correction for Road Segmentation Using Road-side Cameras
Henrik Toikka, Eerik Alamikkotervo, Risto Ojala
Reliable road segmentation in all weather conditions is critical for intelligent transportation applications, autonomous vehicles and advanced driver's assistance systems. For robu…
Trajectory-based Road Autolabeling with Lidar-Camera Fusion in Winter Conditions
Eerik Alamikkotervo, Henrik Toikka, Kari Tammi +1
Robust road segmentation in all road conditions is required for safe autonomous driving and advanced driver assistance systems. Supervised deep learning methods provide accurate ro…
Road Surface Friction Estimation for Winter Conditions Utilising General Visual Features
Risto Ojala, Eerik Alamikkotervo
In below freezing winter conditions, road surface friction can greatly vary based on the mixture of snow, ice, and water on the road. Friction between the road and vehicle tyres is…
TADAP: Trajectory-Aided Drivable area Auto-labeling with Pre-trained self-supervised features in winter driving conditions
Eerik Alamikkotervo, Risto Ojala, Alvari Seppänen +1
Detection of the drivable area in all conditions is crucial for autonomous driving and advanced driver assistance systems. However, the amount of labeled data in adverse driving co…