Lakshman Balasubramanian

Orcid: 0000-0003-1007-2887

According to our database1, Lakshman Balasubramanian authored at least 12 papers between 2021 and 2025.

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

Timeline

2021
2022
2023
2024
2025
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Links

On csauthors.net:

Bibliography

2025
Hybrid Machine Learning Model with a Constrained Action Space for Trajectory Prediction.
CoRR, January, 2025

2024
Open-Set Object Detection for the Identification and Localization of Dissimilar Novel Classes by means of Infrastructure Sensors.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

Clustering and Anomaly Detection in Embedding Spaces for the Validation of Automotive Sensors.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

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

Metric Learning Based Class Specific Experts for Open-Set Recognition of Traffic Participants in Urban Areas Using Infrastructure Sensors.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2023

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

Data Collection and Safety Use Cases in Smart Infrastructures.
Proceedings of the Adjunct Proceedings of the 15th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, 2023

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

Open-Set Recognition based on the Combination of Deep Learning and Ensemble Method for Detecting Unknown Traffic Scenarios.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2021


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