Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Visual Estimation of Building Condition with Patch-level ConvNets   The condition of a building is an important factor for real estate valuation.
Currently, the estimation of condition is determined by real estate appraisers
which makes it subjective to a certain degree. We propose a novel vision-based
approach for the assessment of the building condition from exterior views of
the building. To this end, we develop a multi-scale patch-based pattern
extraction approach and combine it with convolutional neural networks to
estimate building condition from visual clues. Our evaluation shows that
visually estimated building condition can serve as a proxy for condition
estimates by appraisers.

25
The categories of this paper are: patt-sol
16
The categories of this paper are: stat
18
The categories of this paper are: econ
21
The categories of this paper are: adap-org
28
The categories of this paper are: alg-geom
27
The categories of this paper are: comp-gas
15
The categories of this paper are: nucl-ex
33
The categories of this paper are: plasm-ph
24
The categories of this paper are: dg-ga
7
The categories of this paper are: hep-th
22
The categories of this paper are: chao-dyn
8
The categories of this paper are: hep-ex
34
The categories of this paper are: chem-ph
17
The categories of this paper are: q-fin
26
The categories of this paper are: bayes-an
23
The categories of this paper are: solv-int