Essays about: "Semantisk Segmentering"
Showing result 6 - 10 of 57 essays containing the words Semantisk Segmentering.
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6. Self-supervised pre-training of an attention-based model for 3D medical image segmentation
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Accurate segmentation of anatomical structures is crucial for radiation therapy in cancer treatment. Deep learning methods have been demonstrated effective for segmentation of 3D medical images, establishing the current standard. However, they require large amounts of labelled data and suffer from reduced performance on domain shift. READ MORE
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7. Skyline Delineation for Localization in Occluded Environments : Improved Skyline Delineation using Environmental Context from Deep Learning-based Semantic Segmentation
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This thesis addresses the problem of improving the delineation of skylines, also referred to as skyline detection, in occluded and challenging environments where existing skyline delineation methods may struggle or fail. Delineated skylines can be used in monocular camera localization methods by comparing delineated skylines to digital elevation model data to estimate a position based on known terrain. READ MORE
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8. Semi-Supervised Domain Adaptation for Semantic Segmentation with Consistency Regularization : A learning framework under scarce dense labels
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Learning from unlabeled data is a topic of critical significance in machine learning, as the large datasets required to train ever-growing models are costly and impractical to annotate. Semi-Supervised Learning (SSL) methods aim to learn from a few labels and a large unlabeled dataset. READ MORE
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9. Camera ISP optimization for computer vision tasks performed by deep neural networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This thesis aims to improve the performance of Deep Neural Networkss (DNNs) in Computer Vision tasks by optimizing the Image Signal Processor (ISP) parameters. The research investigates the use of simulated RAW images and the application of the DRL-ISP (Deep Reinforcement Learning for Image Signal Processor) method to enhance the accuracy and robustness of DNNs. READ MORE
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10. A Deep Learning Based Approach to Object Recognition from LiDAR Data Along Swedish Railroads
University essay from KTH/Fastigheter och byggandeAbstract : Malfunction in the overhead contact line system is a common cause of disturbances in the train traffic in Sweden. Due to the preventive methods being inefficient, the Swedish Transport Administration has stated the need to develop the railroad maintenance services and has identified Artificial Intelligence (AI) as an important tool for this undertaking. READ MORE
