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2020 – today
- 2024
[c43]Marion Neumeier, Sebastian Dorn, Michael Botsch, Wolfgang Utschick:
Reliable Trajectory Prediction and Uncertainty Quantification with Conditioned Diffusion Models. CVPR Workshops 2024: 3461-3470- [c42]Alexander Fertig
, Lakshman Balasubramanian, Michael Botsch:
Clustering and Anomaly Detection in Embedding Spaces for the Validation of Automotive Sensors. IV 2024: 1076-1083 - [c41]Karthikeyan Chandra Sekaran, Lakshman Balasubramanian, Michael Botsch, Wolfgang Utschick:
Open-Set Object Detection for the Identification and Localization of Dissimilar Novel Classes by means of Infrastructure Sensors. IV 2024: 1643-1650 - [i18]Marion Neumeier, Sebastian Dorn, Michael Botsch, Wolfgang Utschick:
Reliable Trajectory Prediction and Uncertainty Quantification with Conditioned Diffusion Models. CoRR abs/2405.14384 (2024) - 2023
- [j6]Alberto Flores Fernández, Eduardo Sánchez Morales, Michael Botsch, Christian Facchi, Andrés García Higuera:
Generation of Correction Data for Autonomous Driving by Means of Machine Learning and On-Board Diagnostics. Sensors 23(1): 159 (2023) - [j5]Lakshman Balasubramanian, Jonas Wurst, Michael Botsch, Ke Deng:
Open-World Learning for Traffic Scenarios Categorisation. IEEE Trans. Intell. Veh. 8(5): 3506-3521 (2023) - [c40]Michael Botsch, Werner Huber, Lakshman Balasubramanian, Alberto Flores Fernández, Markus Geisler, Christian Gudera, Mauricio Rene Morales Gomez, Peter Riegl, Eduardo Sánchez Morales, Karthikeyan Chandra Sekaran:
Data Collection and Safety Use Cases in Smart Infrastructures. AutomotiveUI (Adjunct Proceedings) 2023: 333-336 - [c39]Marion Neumeier, Sebastian Dorn, Michael Botsch, Wolfgang Utschick:
Prediction and Interpretation of Vehicle Trajectories in the Graph Spectral Domain. ITSC 2023: 1172-1179 - [c38]Parthasarathy Nadarajan, Michael Botsch, Sebastian Sardiña:
Continuous Probabilistic Motion Prediction Based on Latent Space Interpolation. ITSC 2023: 3796-3803 - [c37]Lakshman Balasubramanian, Jonas Wurst, Robin Egolf, Michael Botsch, Wolfgang Utschick, Ke Deng:
SceneDiffusion: Conditioned Latent Diffusion Models for Traffic Scene Prediction. ITSC 2023: 3914-3921 - [c36]Marion Neumeier, Andreas Tollkühn, Sebastian Dorn, Michael Botsch, Wolfgang Utschick:
Optimization and Interpretability of Graph Attention Networks for Small Sparse Graph Structures in Automotive Applications. IV 2023: 1-8 - [c35]Karthikeyan Chandra Sekaran, Lakshman Balasubramanian, Michael Botsch, Wolfgang Utschick:
Metric Learning Based Class Specific Experts for Open-Set Recognition of Traffic Participants in Urban Areas Using Infrastructure Sensors. IV 2023: 1-8 - [i17]Marion Neumeier, Andreas Tollkühn, Sebastian Dorn, Michael Botsch, Wolfgang Utschick:
Gradient Derivation for Learnable Parameters in Graph Attention Networks. CoRR abs/2304.10939 (2023) - [i16]Marion Neumeier, Andreas Tollkühn, Michael Botsch, Wolfgang Utschick:
A Multidimensional Graph Fourier Transformation Neural Network for Vehicle Trajectory Prediction. CoRR abs/2305.07416 (2023) - [i15]Marion Neumeier, Andreas Tollkühn, Sebastian Dorn, Michael Botsch, Wolfgang Utschick:
Optimization and Interpretability of Graph Attention Networks for Small Sparse Graph Structures in Automotive Applications. CoRR abs/2305.16196 (2023) - [i14]Marion Neumeier, Sebastian Dorn, Michael Botsch, Wolfgang Utschick:
Prediction and Interpretation of Vehicle Trajectories in the Graph Spectral Domain. CoRR abs/2309.16702 (2023) - 2022
- [j4]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): 02:1-02:27 (2022) - [j3]Alberto Flores Fernández, Jonas Wurst, Eduardo Sánchez Morales, Michael Botsch, Christian Facchi, Andrés García Higuera:
Probabilistic Traffic Motion Labeling for Multi-Modal Vehicle Route Prediction. Sensors 22(12): 4498 (2022) - [c34]Marion Neumeier, Andreas Tollkühn, Michael Botsch, Wolfgang Utschick:
A Multidimensional Graph Fourier Transformation Neural Network for Vehicle Trajectory Prediction. ITSC 2022: 687-694 - [c33]Tim Elter, Tobias Dirndorfer, Michael Botsch, Wolfgang Utschick:
Interaction-aware Prediction of Occupancy Regions based on a POMDP Framework. ITSC 2022: 980-987 - [c32]Lakshman Balasubramanian, Jonas Wurst, Robin Egolf, Michael Botsch, Wolfgang Utschick, Ke Deng:
ExAgt: Expert-guided Augmentation for Representation Learning of Traffic Scenarios. ITSC 2022: 1471-1478 - [c31]Jonas Wurst, Lakshman Balasubramanian, Michael Botsch, Wolfgang Utschick:
Expert-LaSTS: Expert-Knowledge Guided Latent Space for Traffic Scenarios. IV 2022: 484-491 - [i13]Lakshman Balasubramanian, Jonas Wurst, Robin Egolf, Michael Botsch, Wolfgang Utschick, Ke Deng:
ExAgt: Expert-guided Augmentation for Representation Learning of Traffic Scenarios. CoRR abs/2207.08609 (2022) - [i12]Jonas Wurst, Lakshman Balasubramanian, Michael Botsch, Wolfgang Utschick:
Expert-LaSTS: Expert-Knowledge Guided Latent Space for Traffic Scenarios. CoRR abs/2207.09120 (2022) - 2021
- [j2]Eduardo Sánchez Morales, Julian Dauth, Bertold Huber, Andrés García Higuera, Michael Botsch:
High Precision Outdoor and Indoor Reference State Estimation for Testing Autonomous Vehicles. Sensors 21(4): 1131 (2021) - [c30]Oliver Gallitz, Oliver De Candido, Michael Botsch, Wolfgang Utschick:
Interpretable Early Prediction of Lane Changes Using a Constrained Neural Network Architecture. ITSC 2021: 493-499 - [c29]Marion Neumeier, Michael Botsch, Andreas Tollkühn, Thomas Berberich:
Variational Autoencoder-Based Vehicle Trajectory Prediction with an Interpretable Latent Space. ITSC 2021: 820-827 - [c28]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: 674-681 - [c27]Lakshman Balasubramanian, Jonas Wurst, Michael Botsch, Ke Deng:
Traffic Scenario Clustering by Iterative Optimisation of Self-Supervised Networks Using a Random Forest Activation Pattern Similarity. IV 2021: 682-689 - [c26]Jonas Wurst, Lakshman Balasubramanian, Michael Botsch, Wolfgang Utschick:
Novelty Detection and Analysis of Traffic Scenario Infrastructures in the Latent Space of a Vision Transformer-Based Triplet Autoencoder. IV 2021: 1304-1311 - [i11]Marion Neumeier, Andreas Tollkühn, Thomas Berberich, Michael Botsch:
Variational Autoencoder-Based Vehicle Trajectory Prediction with an Interpretable Latent Space. CoRR abs/2103.13726 (2021) - [i10]Jonas Wurst, Lakshman Balasubramanian, Michael Botsch, Wolfgang Utschick:
Novelty Detection and Analysis of Traffic Scenario Infrastructures in the Latent Space of a Vision Transformer-Based Triplet Autoencoder. CoRR abs/2105.01924 (2021) - [i9]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 abs/2105.07635 (2021) - [i8]Lakshman Balasubramanian, Jonas Wurst, Michael Botsch, Ke Deng:
Traffic Scenario Clustering by Iterative Optimisation of Self-Supervised Networks Using a Random Forest Activation Pattern Similarity. CoRR abs/2105.07639 (2021) - 2020
- [c25]Oliver Gallitz, Oliver De Candido, Michael Botsch, Ron Melz, Wolfgang Utschick:
Interpretable Machine Learning Structure for an Early Prediction of Lane Changes. ICANN (1) 2020: 337-349 - [c24]Oliver De Candido, Michael Koller, Oliver Gallitz, Ron Melz, Michael Botsch, Wolfgang Utschick:
Towards Feature Validation in Time to Lane Change Classification using Deep Neural Networks. ITSC 2020: 1-8 - [c23]Jonas Wurst, Alberto Flores Fernández, Michael Botsch, Wolfgang Utschick:
An Entropy Based Outlier Score and its Application to Novelty Detection for Road Infrastructure Images. IV 2020: 1436-1443 - [c22]Eduardo Sánchez Morales, Friedrich Kruber, Michael Botsch, Bertold Huber, Andrés García Higuera:
Accuracy Characterization of the Vehicle State Estimation from Aerial Imagery. IV 2020: 2081-2088 - [c21]Friedrich Kruber, Eduardo Sánchez Morales, Samarjit Chakraborty, Michael Botsch:
Vehicle Position Estimation with Aerial Imagery from Unmanned Aerial Vehicles. IV 2020: 2089-2096 - [i7]Friedrich Kruber, Jonas Wurst, Michael Botsch:
An Unsupervised Random Forest Clustering Technique for Automatic Traffic Scenario Categorization. CoRR abs/2004.02121 (2020) - [i6]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 abs/2004.02126 (2020) - [i5]Friedrich Kruber, Eduardo Sánchez Morales, Samarjit Chakraborty, Michael Botsch:
Vehicle Position Estimation with Aerial Imagery from Unmanned Aerial Vehicles. CoRR abs/2004.08206 (2020) - [i4]Eduardo Sánchez Morales, Richard Membarth, Andreas Gaull, Philipp Slusallek, Tobias Dirndorfer, Alexander Kammenhuber, Christoph Lauer, Michael Botsch:
Parallel Multi-Hypothesis Algorithm for Criticality Estimation in Traffic and Collision Avoidance. CoRR abs/2005.06773 (2020) - [i3]Eduardo Sánchez Morales, Michael Botsch, Bertold Huber, Andrés García Higuera:
High Precision Indoor Navigation for Autonomous Vehicles. CoRR abs/2005.06791 (2020) - [i2]Eduardo Sánchez Morales, Michael Botsch, Bertold Huber, Andrés García Higuera:
High precision indoor positioning by means of LiDAR. CoRR abs/2005.06798 (2020) - [i1]Jonas Wurst, Alberto Flores Fernández, Michael Botsch, Wolfgang Utschick:
An Entropy Based Outlier Score and its Application to Novelty Detection for Road Infrastructure Images. CoRR abs/2005.13288 (2020)
2010 – 2019
- 2019
- [c20]Amit Chaulwar, Hussein Al-Hashimi, Michael Botsch, Wolfgang Utschick:
Efficient Hybrid Machine Learning Algorithm for Trajectory Planning in Critical Traffic-Scenarios. ICITE 2019: 196-202 - [c19]Eduardo Sánchez Morales, Michael Botsch, Bertold Huber, Andrés García Higuera:
High Precision Indoor Navigation for Autonomous Vehicles. IPIN 2019: 1-8 - [c18]Oliver Gallitz, Oliver De Candido, Michael Botsch, Wolfgang Utschick:
Interpretable Feature Generation using Deep Neural Networks and its Application to Lane Change Detection. ITSC 2019: 3405-3411 - [c17]Eduardo Sánchez Morales, Richard Membarth, Andreas Gaull, Philipp Slusallek, Tobias Dirndorfer, Alexander Kammenhuber, Christoph Lauer, Michael Botsch:
Parallel Multi-Hypothesis Algorithm for Criticality Estimation in Traffic and Collision Avoidance. IV 2019: 2164-2171 - [c16]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: 2463-2470 - 2018
- [c15]Amit Chaulwar, Michael Botsch, Wolfgang Utschick:
Generation of Reference Trajectories for Safe Trajectory Planning. ICANN (1) 2018: 423-434 - [c14]Valentín Cañas, Eduardo Sánchez Morales, Michael Botsch, Andrés García:
Wireless Communication System for the Validation of Autonomous Driving Functions on Full-Scale Vehicles. ICVES 2018: 1-6 - [c13]Marcus Müller, Xing Longl, Michael Botsch, Dennis Böhmländer, Wolfgang Utschick:
Real-Time Crash Severity Estimation with Machine Learning and 2D Mass-Spring-Damper Model. ITSC 2018: 2036-2043 - [c12]Friedrich Kruber, Jonas Wurst, Michael Botsch:
An Unsupervised Random Forest Clustering Technique for Automatic Traffic Scenario Categorization. ITSC 2018: 2811-2818 - 2017
- [j1]Gennaro Notomista, Michael Botsch:
A Machine Learning Approach for the Segmentation of Driving Maneuvers and its Application in Autonomous Parking. J. Artif. Intell. Soft Comput. Res. 7(4): 243 (2017) - [c11]Parthasarathy Nadarajan, Michael Botsch, Sebastian Sardiña:
Predicted-occupancy grids for vehicle safety applications based on autoencoders and the Random Forest algorithm. IJCNN 2017: 1244-1251 - [c10]Amit Chaulwar, Michael Botsch, Wolfgang Utschick:
A machine learning based biased-sampling approach for planning safe trajectories in complex, dynamic traffic-scenarios. Intelligent Vehicles Symposium 2017: 297-303 - 2016
- [c9]Amit Chaulwar, Michael Botsch, Wolfgang Utschick:
A Hybrid Machine Learning Approach for Planning Safe Trajectories in Complex Traffic-Scenarios. ICMLA 2016: 540-546 - [c8]Marcus Müller, Parthasarathy Nadarajan, Michael Botsch, Wolfgang Utschick, Dennis Böhmländer, Stefan Katzenbogen:
A statistical learning approach for estimating the reliability of crash severity predictions. ITSC 2016: 2199-2206 - [c7]Parthasarathy Nadarajan, Michael Botsch:
Probability estimation for Predicted-Occupancy Grids in vehicle safety applications based on machine learning. Intelligent Vehicles Symposium 2016: 1285-1292 - 2015
- [c6]Gennaro Notomista, Michael Botsch:
Maneuver segmentation for autonomous parking based on ensemble learning. IJCNN 2015: 1-8 - [c5]Stephan Herrmann, Wolfgang Utschick, Michael Botsch, Frank Keck:
Supervised Learning via Optimal Control Labeling for Criticality Classification in Vehicle Active Safety. ITSC 2015: 2024-2031 - 2010
- [c4]Michael Reichel, Michael Botsch, Robert Rauschecker, Karl-Heinz Siedersberger, Markus Maurer:
Situation aspect modelling and classification using the Scenario Based Random Forest algorithm for convoy merging situations. ITSC 2010: 360-366 - [c3]Michael Botsch, Christoph Lauer:
Complexity reduction using the Random Forest classifier in a collision detection algorithm. Intelligent Vehicles Symposium 2010: 1228-1235
2000 – 2009
- 2008
- [c2]Michael Botsch, Josef A. Nossek:
Construction of interpretable Radial Basis Function classifiers based on the Random Forest kernel. IJCNN 2008: 220-227 - 2007
- [c1]Michael Botsch, Josef A. Nossek:
Feature Selection for Change Detection in Multivariate Time-Series. CIDM 2007: 590-597
Coauthor Index
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