Jonas Wurst

According to our database, Jonas Wurst authored at least 12 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Domain Knowledge Guided Representation Learning for Traffic Scenarios (Domänenwissen gestützte Repräsentations-Lernverfahren für Verkehrsszenarien)

Jonas Wurst

PhD thesis, 2024

2023

Open-World Learning for Traffic Scenarios Categorisation.

Lakshman Balasubramanian, Jonas Wurst, Michael Botsch, Ke Deng

IEEE Trans. Intell. Veh., May, 2023

SceneDiffusion: Conditioned Latent Diffusion Models for Traffic Scene Prediction.

Lakshman Balasubramanian, Jonas Wurst, Robin Egolf, Michael Botsch, Wolfgang Utschick, Ke Deng

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023

2022

Probabilistic Traffic Motion Labeling for Multi-Modal Vehicle Route Prediction.

Alberto Flores Fernández, Jonas Wurst, Eduardo Sánchez Morales, Michael Botsch, Christian Facchi, Andrés García Higuera

Sensors, 2022

Micro- and Macroscopic Road Traffic Analysis using Drone Image Data.

Friedrich Kruber, Eduardo Sánchez Morales, Robin Egolf, Jonas Wurst, Samarjit Chakraborty, Michael Botsch

Leibniz Trans. Embed. Syst., 2022

Expert-LaSTS: Expert-Knowledge Guided Latent Space for Traffic Scenarios.

Jonas Wurst, Lakshman Balasubramanian, Michael Botsch, Wolfgang Utschick

Proceedings of the 2022 IEEE Intelligent Vehicles Symposium, 2022

ExAgt: Expert-guided Augmentation for Representation Learning of Traffic Scenarios.

Lakshman Balasubramanian, Jonas Wurst, Robin Egolf, Michael Botsch, Wolfgang Utschick, Ke Deng

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022

2021

Novelty Detection and Analysis of Traffic Scenario Infrastructures in the Latent Space of a Vision Transformer-Based Triplet Autoencoder.

Jonas Wurst, Lakshman Balasubramanian, Michael Botsch, Wolfgang Utschick

Proceedings of the IEEE Intelligent Vehicles Symposium, 2021

Traffic Scenario Clustering by Iterative Optimisation of Self-Supervised Networks Using a Random Forest Activation Pattern Similarity.

Lakshman Balasubramanian, Jonas Wurst, Michael Botsch, Ke Deng

Proceedings of the IEEE Intelligent Vehicles Symposium, 2021

2020

An Entropy Based Outlier Score and its Application to Novelty Detection for Road Infrastructure Images.

Jonas Wurst, Alberto Flores Fernández, Michael Botsch, Wolfgang Utschick

Proceedings of the IEEE Intelligent Vehicles Symposium, 2020

2019

Unsupervised and Supervised Learning with the Random Forest Algorithm for Traffic Scenario Clustering and Classification.

Friedrich Kruber, Jonas Wurst, Eduardo Sánchez Morales, Samarjit Chakraborty, Michael Botsch

Proceedings of the 2019 IEEE Intelligent Vehicles Symposium, 2019

2018

An Unsupervised Random Forest Clustering Technique for Automatic Traffic Scenario Categorization.

Friedrich Kruber, Jonas Wurst, Michael Botsch

Proceedings of the 21st International Conference on Intelligent Transportation Systems, 2018