Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Scene learning, recognition and similarity detection in a fuzzy ontology
  via human examples   This paper introduces a Fuzzy Logic framework for scene learning, recognition
and similarity detection, where scenes are taught via human examples. The
framework allows a robot to: (i) deal with the intrinsic vagueness associated
with determining spatial relations among objects; (ii) infer similarities and
dissimilarities in a set of scenes, and represent them in a hierarchical
structure represented in a Fuzzy ontology. In this paper, we briefly formalize
our approach and we provide a few use cases by way of illustration.
Nevertheless, we discuss how the framework can be used in real-world scenarios.

19
The categories of this paper are: eess
24
The categories of this paper are: dg-ga
10
The categories of this paper are: q-bio
37
The categories of this paper are: supr-con
32
The categories of this paper are: atom-ph
36
The categories of this paper are: cmp-lg
16
The categories of this paper are: stat
33
The categories of this paper are: plasm-ph
0
The categories of this paper are: hep-ph
17
The categories of this paper are: q-fin
3
The categories of this paper are: physics
5
The categories of this paper are: gr-qc
22
The categories of this paper are: chao-dyn
8
The categories of this paper are: hep-ex
14
The categories of this paper are: math-ph
34
The categories of this paper are: chem-ph