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1	Deep Learning Semantic Segmentation of 3D Point Cloud Data from a Photon Counting LiDAR / Djupinlärning för semantisk segmentering av 3D punktmoln från en fotonräknande LiDAR Süsskind, Caspian January 2022 (has links) Deep learning has shown to be successful on the task of semantic segmentation of three-dimensional (3D) point clouds, which has many interesting use cases in areas such as autonomous driving and defense applications. A common type of sensor used for collecting 3D point cloud data is Light Detection and Ranging (LiDAR) sensors. In this thesis, a time-correlated single-photon counting (TCSPC) LiDAR is used, which produces very accurate measurements over long distances up to several kilometers. The dataset collected by the TCSPC LiDAR used in the thesis contains two classes, person and other, and it comes with several challenges due to it being limited in terms of size and variation, as well as being extremely class imbalanced. The thesis aims to identify, analyze, and evaluate state-of-the-art deep learning models for semantic segmentation of point clouds produced by the TCSPC sensor. This is achieved by investigating different loss functions, data variations, and data augmentation techniques for a selected state-of-the-art deep learning architecture. The results showed that loss functions tailored for extremely imbalanced datasets performed the best with regard to the metric mean intersection over union (mIoU). Furthermore, an improvement in mIoU could be observed when some combinations of data augmentation techniques were employed. In general, the performance of the models varied heavily, with some achieving promising results and others achieving much worse results. Deep Learning Machine Learning Computer vision Semantic Segmentation Photon Counting LiDAR LiDAR Point Cloud 3D Data Point Cloud Segmentation Point Classification Convolutional Neural Network CNN SPVCNN Djupinlärning LiDAR fotonräknande LiDAR semantisk segmentering datorseende punktmoln maskininlärning

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Deep Learning Semantic Segmentation of 3D Point Cloud Data from a Photon Counting LiDAR / Djupinlärning för semantisk segmentering av 3D punktmoln från en fotonräknande LiDAR