76 citations · 103 across the 15 of their papers we have counts for
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cs.CV2023
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…
cs.CV2023★ 17 cited
Lightweight Regression Model with Prediction Interval Estimation for Computer Vision-based Winter Road Surface Condition Monitoring
Risto Ojala, Alvari Seppänen
Winter conditions pose several challenges for automated driving applications. A key challenge during winter is accurate assessment of road surface condition, as its impact on frict…
cs.CV2023★ 7 cited
Multi-Echo Denoising in Adverse Weather
Alvari Seppänen, Risto Ojala, Kari Tammi
Adverse weather can cause noise to light detection and ranging (LiDAR) data. This is a problem since it is used in many outdoor applications, e.g. object detection and mapping. We…