Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Latent hypernet: Exploring all Layers from Convolutional Neural Networks   Since Convolutional Neural Networks (ConvNets) are able to simultaneously
learn features and classifiers to discriminate different categories of
activities, recent works have employed ConvNets approaches to perform human
activity recognition (HAR) based on wearable sensors, allowing the removal of
expensive human work and expert knowledge. However, these approaches have their
power of discrimination limited mainly by the large number of parameters that
compose the network and the reduced number of samples available for training.
Inspired by this, we propose an accurate and robust approach, referred to as
Latent HyperNet (LHN). The LHN uses feature maps from early layers (hyper) and
projects them, individually, onto a low dimensionality space (latent). Then,
these latent features are concatenated and presented to a classifier. To
demonstrate the robustness and accuracy of the LHN, we evaluate it using four
different networks architectures in five publicly available HAR datasets based
on wearable sensors, which vary in the sampling rate and number of activities.
Our experiments demonstrate that the proposed LHN is able to produce rich
information, improving the results regarding the original ConvNets.
Furthermore, the method outperforms existing state-of-the-art methods.

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The categories of this paper are: comp-gas
34
The categories of this paper are: chem-ph
35
The categories of this paper are: mtrl-th
10
The categories of this paper are: q-bio
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The categories of this paper are: bayes-an
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The categories of this paper are: eess
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The categories of this paper are: q-fin
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The categories of this paper are: gr-qc
3
The categories of this paper are: physics
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The categories of this paper are: chao-dyn
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The categories of this paper are: q-alg
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The categories of this paper are: plasm-ph
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The categories of this paper are: atom-ph
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The categories of this paper are: nucl-th
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The categories of this paper are: patt-sol
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The categories of this paper are: stat