Contribution to Object Extraction in Cartography : A Novel Deep Learning-Based Solution to Recognise, Segment and Post-Process the Road Transport Network as a Continuous Geospatial Element in High-Resolution Aerial Orthoimagery
| Autor: | |
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| Tipo de recurso: | tesis doctoral |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universidad Politécnica de Madrid |
| Repositorio: | Archivo Digital UPM |
| OAI Identifier: | oai:oa.upm.es:70152 |
| Acceso en línea: | https://oa.upm.es/70152/ |
| Access Level: | acceso abierto |
| Palabra clave: | Aerial Orthoimagery Artificial Neural Network Computer Vision Conditional learning Convolutional Neural Network Deep Learning Ensemble learning Generative Adversarial Network Generative Learning Image Analysis Image Classification Image Inpainting Image Post-processing Image-to-Image Translation Remote Sensing Residual Learning Road Extraction Road Recognition Road Surface Area Segmentation models Semantic Segmentation Supervised Learning Transfer Learning Unsupervised Learning Web-based Segmentation Solution |
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