Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An Ensemble of Knowledge Sharing Models for Dynamic Hand Gesture
  Recognition   The focus of this paper is dynamic gesture recognition in the context of the
interaction between humans and machines. We propose a model consisting of two
sub-networks, a transformer and an ordered-neuron long-short-term-memory
(ON-LSTM) based recurrent neural network (RNN). Each sub-network is trained to
perform the task of gesture recognition using only skeleton joints. Since each
sub-network extracts different types of features due to the difference in
architecture, the knowledge can be shared between the sub-networks. Through
knowledge distillation, the features and predictions from each sub-network are
fused together into a new fusion classifier. In addition, a cyclical learning
rate can be used to generate a series of models that are combined in an
ensemble, in order to yield a more generalizable prediction. The proposed
ensemble of knowledge-sharing models exhibits an overall accuracy of 86.11%
using only skeleton information, as tested using the Dynamic Hand Gesture-14/28
dataset

30
The categories of this paper are: q-alg
15
The categories of this paper are: nucl-ex
8
The categories of this paper are: hep-ex
9
The categories of this paper are: nlin
2
The categories of this paper are: math
28
The categories of this paper are: alg-geom
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The categories of this paper are: comp-gas
7
The categories of this paper are: hep-th
34
The categories of this paper are: chem-ph
18
The categories of this paper are: econ
16
The categories of this paper are: stat
3
The categories of this paper are: physics
4
The categories of this paper are: cond-mat
33
The categories of this paper are: plasm-ph
35
The categories of this paper are: mtrl-th
10
The categories of this paper are: q-bio