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 6 of 6 for “"Fully Convolutional Network"”.
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Weakly supervised learning from referring expression: Challenge and directions
… from referring expression. Unlike traditional fully supervised semantic segmentation of object recognition tasks, in which a a small set of discrete class bases is provided, the referring expression task is performed associated with a sentence phrase, e.g. “the dude on the dolphin”. Previous …
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Geometrically and Temporally Consistent Robot Perception
… with the development of an end-to-end neural network model for 6D object pose estimation. The model applies a 3D fully-convolutional network to extract geometric features and enforces pairwise consistency of features via spectral convolution on a compatibility graph. We then develop a …
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Use of Photogrammetry Aided Damage Detection for Residual Strength Estimation of Corrosion Damaged Prestressed Concrete Bridge Girders
… cracks detected at pixel level using a U-Net (Fully Convolutional Network). Spalls were detected by identifying the locations where normals associated with the points in the 3D point cloud deviated from being perpendicular to the reference directions chosen, by an amount greater than a …
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A deep learning approach to focal cortical dysplasia segmentation in children with medically intractable epilepsy
… of deep learning techniques, specifically Convolutional Neural Networks (CNN), and Fully Convolutional Networks (FCN) are that they are built to extract detailed features in images with minimal user involvement. Therefore, we set to develop a model, which takes an MRI, classifies whether it …
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Autonomous vision-based inspection of RC railway bridges for rapid post-earthquake response and recovery
… recognition, and localization are realized by fully convolutional network (FCN)-based semantic segmentation and depth prediction algorithms. The investigation begins with the bridge component recognition using a single real-world image. Based on the lessons learned from the initial work, the …
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Development of novel optical sensing-based digital stethoscopes and deep learning-based heart sound denoising algorithms
… pipeline for the denoising of heart sounds using fully convolutional networks (FCNs) is proposed, along with a thorough investigation of its capabilities and robustness. Both the hardware and software systems developed in this thesis were designed under the guidance of its co-supervisor, a medical …