9 citations · 15 across the 7 of their papers we have counts for
9 papers
Multispectral airborne laser scanning dataset for tree species classification: MS-ALS-SPECIES
Matti Hyyppä, Klaara Salolahti, Eric Hyyppä +9
The shift from stand-level to individual-tree-level forest assessments supports improved species mapping and biodiversity monitoring, particularly in boreal ecosystems where tree s…
Deep Learning-based Robust Autonomous Navigation of Aerial Robots in Dense Forests
Guglielmo Del Col, Väinö Karjalainen, Teemu Hakala +2
Autonomous aerial navigation in dense natural environments remains challenging due to limited visibility, thin and irregular obstacles, GNSS-denied operation, and frequent perceptu…
Field evaluation and optimization of a lightweight autonomous lidar-based UAV system based on a rigorous experimental setup in boreal forest environments
Aleksi Karhunen, Teemu Hakala, Väinö Karjalainen +1
Interest in utilizing autonomous uncrewed aerial vehicles (UAVs) for under-canopy forest remote sensing has increased in recent years, resulting in the publication of numerous auto…
Benchmarking individual tree segmentation using multispectral airborne laser scanning data: the FGI-EMIT dataset
Lassi Ruoppa, Tarmo Hietala, Verneri Seppänen +6
Individual tree segmentation (ITS) from LiDAR point clouds is fundamental for applications such as forest inventory, carbon monitoring and biodiversity assessment. Traditionally, I…
Towards autonomous photogrammetric forest inventory using a lightweight under-canopy robotic drone
Väinö Karjalainen, Niko Koivumäki, Teemu Hakala +5
Drones are increasingly used in forestry to capture high-resolution remote sensing data, supporting enhanced monitoring, assessment, and decision-making processes. While operations…
Unsupervised semantic segmentation of urban high-density multispectral point clouds
Oona Oinonen, Lassi Ruoppa, Josef Taher +7
The availability of highly accurate urban airborne laser scanning (ALS) data will increase rapidly in the future, especially as acquisition costs decrease, for example through the…
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…
ICN enabling CoAP Extensions for IP based IoT devices
Nikos Fotiou, George Xylomenos, George C. Polyzos +4
The Constrained Application Protocol (CoAP) and its extensions, such as observe and group communication, offer the potential for developing novel IoT applications. However, a full-…
CoAP over ICN
Nikos Fotiou, Hasan Islam, Dmitrij Lagutin +2
The Constrained Application Protocol (CoAP) is a specialized Web transfer protocol for resource-oriented applications intended to run on constrained devices, typically part of the…