Essays about: "semantic annotations"
Showing result 1 - 5 of 13 essays containing the words semantic annotations.
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1. Toward Equine Gait Analysis : Semantic Segmentation and 3D Reconstruction
University essay from Linköpings universitet/DatorseendeAbstract : Harness racing horses are exposed to high workload and consequently, they are at risk of joint injuries and lameness. In recent years, the interest in applications to improve animal welfare has increased and there is a demand for objective assessment methods that can enable early and robust diagnosis of injuries. READ MORE
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2. Aerial View Image-Goal Localization with Reinforcement Learning
University essay from Lunds universitet/Matematik LTHAbstract : With an increased amount and availability of unmanned aerial vehicles (UAVs) and other remote sensing devices (e.g. satellites) we have recently seen an explosion in computer vision methodologies tailored towards processing and understanding aerial view data. READ MORE
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3. Classification of Terrain Roughness from Nationwide Data Sources Using Deep Learning
University essay from Linköpings universitet/Institutionen för systemteknikAbstract : 3D semantic segmentation is an expanding topic within the field of computer vision, which has received more attention in recent years due to the development of more powerful GPUs and the newpossibilities offered by deep learning techniques. Simultaneously, the amount of available spatial LiDAR data over Sweden has also increased. READ MORE
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4. Deep Learning for Earth Observation: improvement of classification methods for land cover mapping : Semantic segmentation of satellite image time series
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Satellite Image Time Series (SITS) are becoming available at high spatial, spectral and temporal resolutions across the globe by the latest remote sensing sensors. These series of images can be highly valuable when exploited by classification systems to produce frequently updated and accurate land cover maps. READ MORE
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5. Learning from Synthetic Data : Towards Effective Domain Adaptation Techniques for Semantic Segmentation of Urban Scenes
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Semantic segmentation is the task of predicting predefined class labels for each pixel in a given image. It is essential in autonomous driving, but also challenging because training accurate models requires large and diverse datasets, which are difficult to collect due to the high cost of annotating images at pixel-level. READ MORE