Essays about: "Bildanalys"
Showing result 31 - 35 of 123 essays containing the word Bildanalys.
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31. Mapping the relationship between integrin activation, focal adhesion organization and mechanotransduction in fibroblasts
University essay from Lunds universitet/Avdelningen för Biomedicinsk teknikAbstract : Cells can sense and respond to mechanical forces through a process called mechanotransduction. It is controlled by the mechanical cues, originated from the cell's microenvironment, and occurs via a complex, step-wise process. READ MORE
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32. Leveraging Adult Fashion to Enhance Children’s Fashion Recognition
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The future of the fashion industry is expected to be online, thus a significant amount of research is being conducted in the field of fashion image analysis. Currently, a task that places a heavy workload on online stores is manually tagging new garments, including attributes such as category, color, pattern, or style. READ MORE
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33. Data Augmentation to Improve Cross-Domain Generalization in Deep Learning MRI Segmentation
University essay from Lunds universitet/Matematik LTHAbstract : Semantic segmentation of medical images is an important task with many applications. However, manually delineating 3D images is time-consuming and the demand for automation is high. For many image segmentation tasks, deep learning has provided state-of-the-art results. READ MORE
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34. Continuous Balance Evaluation by Image Analysis of Live Video : Fall Prevention Through Pose Estimation
University essay from KTH/Skolan för kemi, bioteknologi och hälsa (CBH)Abstract : The deep learning technique Human Pose Estimation (or Human Keypoint Detection) is a promising field in tracking a person and identifying its posture. As posture and balance are two closely related concepts, the use of human pose estimation could be applied to fall prevention. READ MORE
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35. Ensembles of Single Image Super-Resolution Generative Adversarial Networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Generative Adversarial Networks have been used to obtain state-of-the-art results for low-level computer vision tasks like single image super-resolution, however, they are notoriously difficult to train due to the instability related to the competing minimax framework. Additionally, traditional ensembling mechanisms cannot be effectively applied with these types of networks due to the resources they require at inference time and the complexity of their architectures. READ MORE