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Friedrich Kruber
Publication Activity (10 Years)
Years Active: 2018-2022
Publications (10 Years): 10
Top Topics
Random Forest
Position Estimation
Feature Importance
Aerial Imagery
Top Venues
CoRR
IV
ITSC
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Publications
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Friedrich Kruber
,
Eduardo Sánchez Morales
,
Robin Egolf
,
Jonas Wurst
,
Samarjit Chakraborty
,
Michael Botsch
Micro- and Macroscopic Road Traffic Analysis using Drone Image Data.
Leibniz Trans. Embed. Syst.
8 (1) (2022)
Lakshman Balasubramanian
,
Friedrich Kruber
,
Michael Botsch
,
Ke Deng
Open-Set Recognition based on the Combination of Deep Learning and Ensemble Method for Detecting Unknown Traffic Scenarios.
IV
(2021)
Lakshman Balasubramanian
,
Friedrich Kruber
,
Michael Botsch
,
Ke Deng
Open-set Recognition based on the Combination of Deep Learning and Ensemble Method for Detecting Unknown Traffic Scenarios.
CoRR
(2021)
Friedrich Kruber
,
Jonas Wurst
,
Michael Botsch
An Unsupervised Random Forest Clustering Technique for Automatic Traffic Scenario Categorization.
CoRR
(2020)
Friedrich Kruber
,
Eduardo Sánchez Morales
,
Samarjit Chakraborty
,
Michael Botsch
Vehicle Position Estimation with Aerial Imagery from Unmanned Aerial Vehicles.
IV
(2020)
Friedrich Kruber
,
Eduardo Sánchez Morales
,
Samarjit Chakraborty
,
Michael Botsch
Vehicle Position Estimation with Aerial Imagery from Unmanned Aerial Vehicles.
CoRR
(2020)
Friedrich Kruber
,
Jonas Wurst
,
Eduardo Sánchez Morales
,
Samarjit Chakraborty
,
Michael Botsch
Unsupervised and Supervised Learning with the Random Forest Algorithm for Traffic Scenario Clustering and Classification.
CoRR
(2020)
Eduardo Sánchez Morales
,
Friedrich Kruber
,
Michael Botsch
,
Bertold Huber
,
Andrés García Higuera
Accuracy Characterization of the Vehicle State Estimation from Aerial Imagery.
IV
(2020)
Friedrich Kruber
,
Jonas Wurst
,
Eduardo Sánchez Morales
,
Samarjit Chakraborty
,
Michael Botsch
Unsupervised and Supervised Learning with the Random Forest Algorithm for Traffic Scenario Clustering and Classification.
IV
(2019)
Friedrich Kruber
,
Jonas Wurst
,
Michael Botsch
An Unsupervised Random Forest Clustering Technique for Automatic Traffic Scenario Categorization.
ITSC
(2018)