Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: On the Metrics and Adaptation Methods for Domain Divergences of
  sEMG-based Gesture Recognition   We propose a new metric to measure domain divergence and a new domain
adaptation method for time-series classification. The metric belongs to the
class of probability distributions-based metrics, is transductive, and does not
assume the presence of source data samples. The 2-stage method utilizes an
improved autoregressive, RNN-based architecture with deep/non-linear
transformation. We assess our metric and the performance of our model in the
context of sEMG/EMG-based gesture recognition under inter-session and
inter-subject domain shifts.

18
The categories of this paper are: econ
0
The categories of this paper are: hep-ph
32
The categories of this paper are: atom-ph
7
The categories of this paper are: hep-th
14
The categories of this paper are: math-ph
34
The categories of this paper are: chem-ph
3
The categories of this paper are: physics
15
The categories of this paper are: nucl-ex
22
The categories of this paper are: chao-dyn
27
The categories of this paper are: comp-gas
36
The categories of this paper are: cmp-lg
26
The categories of this paper are: bayes-an
25
The categories of this paper are: patt-sol
10
The categories of this paper are: q-bio
31
The categories of this paper are: ao-sci
21
The categories of this paper are: adap-org