Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Domain Adaptation with L2 constraints for classifying images from
  different endoscope systems   This paper proposes a method for domain adaptation that extends the maximum
margin domain transfer (MMDT) proposed by Hoffman et al., by introducing L2
distance constraints between samples of different domains; thus, our method is
denoted as MMDTL2. Motivated by the differences between the images taken by
narrow band imaging (NBI) endoscopic devices, we utilize different NBI devices
as different domains and estimate the transformations between samples of
different domains, i.e., image samples taken by different NBI endoscope
systems. We first formulate the problem in the primal form, and then derive the
dual form with much lesser computational costs as compared to the naive
approach. From our experimental results using NBI image datasets from two
different NBI endoscopic devices, we find that MMDTL2 is better than MMDT and
also support vector machines without adaptation, especially when NBI image
features are high-dimensional and the per-class training samples are greater
than 20.

28
The categories of this paper are: alg-geom
37
The categories of this paper are: supr-con
6
The categories of this paper are: astro-ph
5
The categories of this paper are: gr-qc
33
The categories of this paper are: plasm-ph
27
The categories of this paper are: comp-gas
26
The categories of this paper are: bayes-an
19
The categories of this paper are: eess
9
The categories of this paper are: nlin
7
The categories of this paper are: hep-th
34
The categories of this paper are: chem-ph
29
The categories of this paper are: funct-an
3
The categories of this paper are: physics
23
The categories of this paper are: solv-int
16
The categories of this paper are: stat
13
The categories of this paper are: quant-ph