Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Lung Sound Classification Using Co-tuning and Stochastic Normalization   In this paper, we use pre-trained ResNet models as backbone architectures for
classification of adventitious lung sounds and respiratory diseases. The
knowledge of the pre-trained model is transferred by using vanilla fine-tuning,
co-tuning, stochastic normalization and the combination of the co-tuning and
stochastic normalization techniques. Furthermore, data augmentation in both
time domain and time-frequency domain is used to account for the class
imbalance of the ICBHI and our multi-channel lung sound dataset. Additionally,
we apply spectrum correction to consider the variations of the recording device
properties on the ICBHI dataset. Empirically, our proposed systems mostly
outperform all state-of-the-art lung sound classification systems for the
adventitious lung sounds and respiratory diseases of both datasets.

37
The categories of this paper are: supr-con
2
The categories of this paper are: math
35
The categories of this paper are: mtrl-th
30
The categories of this paper are: q-alg
33
The categories of this paper are: plasm-ph
27
The categories of this paper are: comp-gas
36
The categories of this paper are: cmp-lg
17
The categories of this paper are: q-fin
12
The categories of this paper are: nucl-th
3
The categories of this paper are: physics
21
The categories of this paper are: adap-org
14
The categories of this paper are: math-ph
22
The categories of this paper are: chao-dyn
9
The categories of this paper are: nlin
6
The categories of this paper are: astro-ph
5
The categories of this paper are: gr-qc