Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Subject Independent Emotion Recognition using EEG Signals Employing
  Attention Driven Neural Networks   In the recent past, deep learning-based approaches have significantly
improved the classification accuracy when compared to classical signal
processing and machine learning based frameworks. But most of them were
subject-dependent studies which were not able to generalize on the
subject-independent tasks due to the inter-subject variability present in EEG
data. In this work, a novel deep learning framework capable of doing
subject-independent emotion recognition is presented, consisting of two parts.
First, an unsupervised Long Short-Term Memory (LSTM) with channel-attention
autoencoder is proposed for getting a subject-invariant latent vector subspace
i.e., intrinsic variables present in the EEG data of each individual. Secondly,
a convolutional neural network (CNN) with attention framework is presented for
performing the task of subject-independent emotion recognition on the encoded
lower dimensional latent space representations obtained from the proposed LSTM
with channel-attention autoencoder. With the attention mechanism, the proposed
approach could highlight the significant time-segments of the EEG signal, which
contributes to the emotion under consideration as validated by the results. The
proposed approach has been validated using publicly available datasets for EEG
signals such as DEAP dataset, SEED dataset and CHB-MIT dataset. The proposed
end-to-end deep learning framework removes the requirement of different hand
engineered features and provides a single comprehensive task agnostic EEG
analysis tool capable of performing various kinds of EEG analysis on subject
independent data.

22
The categories of this paper are: chao-dyn
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The categories of this paper are: patt-sol
37
The categories of this paper are: supr-con
10
The categories of this paper are: q-bio
18
The categories of this paper are: econ
6
The categories of this paper are: astro-ph
21
The categories of this paper are: adap-org
11
The categories of this paper are: hep-lat
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
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The categories of this paper are: nucl-th
31
The categories of this paper are: ao-sci
13
The categories of this paper are: quant-ph
20
The categories of this paper are: acc-phys
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The categories of this paper are: plasm-ph