Essays about: "semantic distance"
Showing result 1 - 5 of 25 essays containing the words semantic distance.
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1. Optic nerve sheath diameter semantic segmentation and feature extraction
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Traumatic brain injury (TBI) affects millions of people worldwide, leading to significant mortality and disability rates. Elevated intracranial pressure (ICP) resulting from TBI can cause severe complications and requires early detection to improve patient outcomes. READ MORE
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2. Segmentation, Classification and Tracking of Objects in LiDAR Point Cloud Data Using Deep Learning
University essay from Lunds universitet/Matematik LTHAbstract : The purpose of this thesis was to explore deep learning methods of segmentation, classification and tracking of objects in LiDAR data. To do this a complete pipeline was developed, consisting of background filtering, clustering, tracking, labeling and visualization. READ MORE
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3. Radar Detection Using Deep Learning
University essay from Lunds universitet/Matematik LTHAbstract : This thesis aims to reproduce and improve a paper about dynamic road user detection on 2D bird's-eye-view radar point cloud in the context of autonomous driving. We choose RadarScenes, a recent large public dataset, to train and test deep neural networks. READ MORE
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4. A comparison of different methods in their ability to compare semantic similarity between articles and press releases
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The goal of a press release is to have the information spread as widely as possible. A suitable approach to distribute the information is to target journalists who are likely to distribute the information further. READ MORE
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5. Self-Supervised Learning: Land Classification of Satellite Imagery
University essay from Lunds universitet/Matematisk statistikAbstract : The rise of self-supervised learning has granted a deeper level of generalized machine learning capable of learning semantic representations without any use of labelling. With 700 satellites orbiting Earth and generating terabytes of unlabelled data daily, satellite imagery serves as a particularly enticing data set for self-supervised learning, containing rich information with many applicable domains,such as agriculture. READ MORE