Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Road Segmentation in SAR Satellite Images with Deep Fully-Convolutional
  Neural Networks   Remote sensing is extensively used in cartography. As transportation networks
grow and change, extracting roads automatically from satellite images is
crucial to keep maps up-to-date. Synthetic Aperture Radar satellites can
provide high resolution topographical maps. However roads are difficult to
identify in these data as they look visually similar to targets such as rivers
and railways. Most road extraction methods on Synthetic Aperture Radar images
still rely on a prior segmentation performed by classical computer vision
algorithms. Few works study the potential of deep learning techniques, despite
their successful applications to optical imagery. This letter presents an
evaluation of Fully-Convolutional Neural Networks for road segmentation in SAR
images. We study the relative performance of early and state-of-the-art
networks after carefully enhancing their sensitivity towards thin objects by
adding spatial tolerance rules. Our models shows promising results,
successfully extracting most of the roads in our test dataset. This shows that,
although Fully-Convolutional Neural Networks natively lack efficiency for road
segmentation, they are capable of good results if properly tuned. As the
segmentation quality does not scale well with the increasing depth of the
networks, the design of specialized architectures for roads extraction should
yield better performances.

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The categories of this paper are: astro-ph
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The categories of this paper are: mtrl-th
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The categories of this paper are: chao-dyn
18
The categories of this paper are: econ
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The categories of this paper are: chem-ph
11
The categories of this paper are: hep-lat
23
The categories of this paper are: solv-int
36
The categories of this paper are: cmp-lg
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The categories of this paper are: patt-sol
28
The categories of this paper are: alg-geom
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The categories of this paper are: cond-mat
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The categories of this paper are: physics
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The categories of this paper are: math-ph
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The categories of this paper are: q-alg
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The categories of this paper are: nlin
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The categories of this paper are: eess