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 multi-model sensor fusion for downstream perception tasks in autonomous driving such as object detection and object tracking.
I offer theses in the field of intelligent video analytics at any time.
Completed and Ongoing Theses
- “Performance Analysis of 3D Object Detection Algorithms using the CARLA Simulated Dataset”
- “Investigation of Deep Learning Models for 3D Shape Similarity Matching and Efficient CAD Model Retrieval Algorithms”
Research Internships and Project Theses
- “3D Point Cloud Segmentation based on Normal Feature and Deep Learning”
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. June 2023 - 10. April 2023)
In: International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2023 2023
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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), p. 1825
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Deep learning based F-Mask alternative for Sentinel-2 images in polar regions
EGU General Assembly (, 19. April 2021 - 30. April 2021)
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