Joint height estimation and semantic labeling of monocular aerial images with CNNS

@article{Srivastava2017JointHE,
  title={Joint height estimation and semantic labeling of monocular aerial images with CNNS},
  author={Shivangi Srivastava and Michele Volpi and Devis Tuia},
  journal={2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)},
  year={2017},
  pages={5173-5176}
}
We aim to jointly estimate height and semantically label monocular aerial images. These two tasks are traditionally addressed separately in remote sensing, despite their strong correlation. Therefore, a model learning both height and classes jointly seems advantageous and so, we propose a multitask Convolutional Neural Network (CNN) architecture with two losses: one performing semantic labeling, and another predicting normalized Digital Surface Model (nDSM) from the pixel values. Since the nDSM… CONTINUE READING
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