Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 7 of 7 for “"Class Segmentation"”.
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Multi-class segmentation of brain tumor using Convolution Neural Network
… (MR) images. Due to the challenges in manual segmentation, computerized brain tumor segmentation is one of the most important challenges in medical imaging. The fully convolutional structure of the network makes it faster than any network with a dense fully connected layer. The two phase …
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Multi-Class 3D Segmentation of Progressive Damage in Advanced Composites using Deep Learning
… is normally analyzed by manual or semi-automated segmentation techniques, where a user identifies and segments the different damage modes (e.g., internal cracks) in the 2D tomograms that comprise the 3D tomographic scan. However, these scans contain a large amount of data (≈10 GB/mm3 ) making it …
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Deep Learning of Semantic Image Labels on HDR Imagery in a Maritime Environment
… This study creates labels for a multi-class semantic segmentation process, and performs well on water and horizon identification in the littoral zone. Additionally, this work contributes proof that water can be reasonably identified using HDR imagery with semantic networks, which is …
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Fully Automated Segmentation of High Grade Serous Ovarian Cancer on Computed Tomography Images using Deep Learning
… networks can be used for the fully automated segmentation of high grade serous ovarian cancer. The recent rise of deep learning has pushed the limits of what algorithms can achieve in fields of image analysis, such as the task of segmentation. The field of medical image segmentation has …
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Advanced Radar Sounder Data Analysis Methods under Limited labeled Data Constraints
… To address this challenge, several automatic classification methods have been developed. However, most of them depend on large labeled datasets and work only when trained and tested on data from the same campaign, which limits their ability to generalize to new environments. This creates the …
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Recognition, reorganisation, reconstruction and reinteraction for scene understanding
… Understanding. It consists of solving three classical computer vision problems: recognition, reorganisation and reconstruction. In this dissertation, I focus on some of these problems and propose methods for solving them. The work can be divided into three main parts. In the first part, I …
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Automated Object Segmentation in Existing Industrial Facilities
Shape segmentation from point cloud data is a core step of the digital twinning process for industrial facilities. However, this process is labour-intensive with 90% of the cost being spent on converting point cloud data to a model. This counteracts the perceived value of the resulting model in …