Aerial Imagery for Roof Segmentation: A Large-Scale Dataset towards Automatic Mapping of Buildings
arXiv:1807.09532 · doi:10.1016/j.isprsjprs.2018.11.011
Abstract
arXiv admin note: This version has been removed as the user did not have the right to agree to the license at the time of submission
arXiv admin note: This version has been removed as the user did not have the right to agree to the license at the time of submission
References in corpus (10)
- Remote Sensing Image Scene Classification: Benchmark and State of the Art
- AID: A Benchmark Dataset for Performance Evaluation of Aerial Scene Classification
- DeepGlobe 2018: A Challenge to Parse the Earth through Satellite Images
- Algorithms for Semantic Segmentation of Multispectral Remote Sensing Imagery using Deep Learning
- PatternNet: A Benchmark Dataset for Performance Evaluation of Remote Sensing Image Retrieval
- Dense semantic labeling of sub-decimeter resolution images with convolutional neural networks
- Land cover mapping at very high resolution with rotation equivariant CNNs: towards small yet accurate models
- Learning Aerial Image Segmentation from Online Maps
- High-Resolution Semantic Labeling with Convolutional Neural Networks
- Deep multi-task learning for a geographically-regularized semantic segmentation of aerial images
Cited by in corpus (7)
- LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation
- A Multi-scale Generalized Shrinkage Threshold Network for Image Blind Deblurring in Remote Sensing
- Interactive Learning for Semantic Segmentation in Earth Observation
- Robust object extraction from remote sensing data
- Building Segmentation through a Gated Graph Convolutional Neural Network with Deep Structured Feature Embedding
- Instance segmentation of buildings using keypoints
- Progressively Growing Generative Adversarial Networks for High Resolution Semantic Segmentation of Satellite Images