Jonas Wurst

Orcid: 0000-0002-0399-3672

According to our database1, Jonas Wurst authored at least 11 papers between 2018 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2023
Open-World Learning for Traffic Scenarios Categorisation.
IEEE Trans. Intell. Veh., May, 2023

SceneDiffusion: Conditioned Latent Diffusion Models for Traffic Scene Prediction.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023

2022
Probabilistic Traffic Motion Labeling for Multi-Modal Vehicle Route Prediction.
Sensors, 2022

Micro- and Macroscopic Road Traffic Analysis using Drone Image Data.
Leibniz Trans. Embed. Syst., 2022

Expert-LaSTS: Expert-Knowledge Guided Latent Space for Traffic Scenarios.
Proceedings of the 2022 IEEE Intelligent Vehicles Symposium, 2022

ExAgt: Expert-guided Augmentation for Representation Learning of Traffic Scenarios.
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.
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.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2021

2020
An Entropy Based Outlier Score and its Application to Novelty Detection for Road Infrastructure Images.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2020

2019
Unsupervised and Supervised Learning with the Random Forest Algorithm for Traffic Scenario Clustering and Classification.
Proceedings of the 2019 IEEE Intelligent Vehicles Symposium, 2019

2018
An Unsupervised Random Forest Clustering Technique for Automatic Traffic Scenario Categorization.
Proceedings of the 21st International Conference on Intelligent Transportation Systems, 2018


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