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Showing result 1 - 5 of 212 essays matching the above criteria.
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1. Night Vision Goggle Simulation in a Mixed Reality Flight Simulator with Seamless Integrated Real World
University essay from Linköpings universitet/Medie- och Informationsteknik; Linköpings universitet/Tekniska fakultetenAbstract : Night vision goggles (NVGs) are optical devices used to enhance human vision at low light conditions such as nighttime. The image seen through the goggles is brightened but with the consequence of introduced visual limitations and illusions. READ MORE
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2. Mutual Enhancement of Environment Recognition and Semantic Segmentation in Indoor Environment
University essay fromAbstract : Background:The dynamic field of computer vision and artificial intelligence has continually evolved, pushing the boundaries in areas like semantic segmentation andenvironmental recognition, pivotal for indoor scene analysis. This research investigates the integration of these two technologies, examining their synergy and implicayions for enhancing indoor scene understanding. READ MORE
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3. Image-classification for Brain Tumor using Pre-trained Convolutional Neural Network
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Brain tumor is a disease characterized by uncontrolled growth of abnormal cells in the brain. The brain is responsible for regulating the functions of all other organs, hence, any atypical growth of cells in the brain can have severe implications for its functions. READ MORE
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4. Quality enhancement of time-resolved computed tomography scans with cycleGAN
University essay from Lunds universitet/Synkrotronljusfysik; Lunds universitet/Fysiska institutionenAbstract : Time-resolved x-ray tomography enables us to dynamically and non-destructively study the interior of a specimen. The obtainable temporal resolution is limited by the x-ray flux and the desired spatial resolution. READ MORE
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5. Domain Adaptation for Multi-Contrast Image Segmentation in Cardiac Magnetic Resonance Imaging
University essay from KTH/Skolan för kemi, bioteknologi och hälsa (CBH)Abstract : Accurate segmentation of the ventricles and myocardium on Cardiac Magnetic Resonance (CMR) images is crucial to assess the functioning of the heart or to diagnose patients suffering from myocardial infarction. However, the domain shift existing between the multiple sequences of CMR data prevents a deep learning model trained on a specific contrast to be used on a different sequence. READ MORE