Nambiar, Kamal Gopikrishnan
Kamal Gopikrishnan Nambiar, M. Sc.
I work in the field of Embedded Perception and my research primarily focuses on the algorithms for processing LiDAR point cloud data. LiDAR point clouds are three-dimensional representations of the surrounding environment, acquired using specialized sensors, and find applications in various fields including remote sensing and autonomous driving. The goal is to develop methods for preprocessing, augmentation, and multimodal sensor fusion for downstream perception tasks in autonomous driving such as object detection and object tracking.
Ich biete jederzeit Abschlussarbeiten im Bereich der intelligenten Videoanalyse an.
Masterarbeiten
- „Leistungsanalyse von Algorithmen zur 3D-Objekterkennung mit dem simulierten CARLA-Datensatz“
- „Evaluierung von Deep-Learning-Algorithmen für Ähnlichkeitsanalyse von 3D-Modellen und effiziente CAD Suchmaschinenoptimierun“
Forschungspraktika/Projektarbeiten
- „3D-Punktwolken-Segmentierung basierend auf Normalenmerkmalen und Deep Learning“
Keine passenden Einträge gefunden.
2025
Deep probabilistic model for lossless scalable point cloud attribute compression (Beitrag bei einer Tagung, accepted)
DOI: 10.48550/arXiv.2303.06517
BibTeX: Download
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2023
DEEP PROBABILISTIC MODEL FOR LOSSLESS SCALABLE POINT CLOUD ATTRIBUTE COMPRESSION
International Conference on Acoustics, Speech, and Signal Processing (ICASSP) (Rodos Palace Luxury Convention Resort, Rhodes Island, Greece, 4. Juni 2023 - 10. April 2023)
In: International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2023 2023
DOI: 10.1109/icassp49357.2023.10095385
URL: https://arxiv.org/abs/2303.06517
BibTeX: Download
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2022
A Self-Trained Model for Cloud, Shadow and Snow Detection in Sentinel-2 Images of Snow- and Ice-Covered Regions
In: Remote Sensing 14 (2022), S. 1825
ISSN: 2072-4292
DOI: 10.3390/rs14081825
BibTeX: Download
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2021
Deep learning based F-Mask alternative for Sentinel-2 images in polar regions
EGU General Assembly (, 19. April 2021 - 30. April 2021)
DOI: 10.5194/egusphere-egu21-15914
BibTeX: Download
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