Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: PyTouch: A Machine Learning Library for Touch Processing   With the increased availability of rich tactile sensors, there is an equally
proportional need for open-source and integrated software capable of
efficiently and effectively processing raw touch measurements into high-level
signals that can be used for control and decision-making. In this paper, we
present PyTouch -- the first machine learning library dedicated to the
processing of touch sensing signals. PyTouch, is designed to be modular,
easy-to-use and provides state-of-the-art touch processing capabilities as a
service with the goal of unifying the tactile sensing community by providing a
library for building scalable, proven, and performance-validated modules over
which applications and research can be built upon. We evaluate PyTouch on
real-world data from several tactile sensors on touch processing tasks such as
touch detection, slip and object pose estimations. PyTouch is open-sourced at
https://github.com/facebookresearch/pytouch .

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The categories of this paper are: math-ph
36
The categories of this paper are: cmp-lg
2
The categories of this paper are: math
35
The categories of this paper are: mtrl-th
20
The categories of this paper are: acc-phys
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The categories of this paper are: ao-sci
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The categories of this paper are: econ
3
The categories of this paper are: physics
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The categories of this paper are: bayes-an
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The categories of this paper are: atom-ph
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The categories of this paper are: stat
22
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: adap-org
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The categories of this paper are: patt-sol
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The categories of this paper are: eess