Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Factors of Transferability for a Generic ConvNet Representation   Evidence is mounting that Convolutional Networks (ConvNets) are the most
effective representation learning method for visual recognition tasks. In the
common scenario, a ConvNet is trained on a large labeled dataset (source) and
the feed-forward units activation of the trained network, at a certain layer of
the network, is used as a generic representation of an input image for a task
with relatively smaller training set (target). Recent studies have shown this
form of representation transfer to be suitable for a wide range of target
visual recognition tasks. This paper introduces and investigates several
factors affecting the transferability of such representations. It includes
parameters for training of the source ConvNet such as its architecture,
distribution of the training data, etc. and also the parameters of feature
extraction such as layer of the trained ConvNet, dimensionality reduction, etc.
Then, by optimizing these factors, we show that significant improvements can be
achieved on various (17) visual recognition tasks. We further show that these
visual recognition tasks can be categorically ordered based on their distance
from the source task such that a correlation between the performance of tasks
and their distance from the source task w.r.t. the proposed factors is
observed.

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The categories of this paper are: q-bio
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The categories of this paper are: atom-ph
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The categories of this paper are: funct-an
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The categories of this paper are: mtrl-th
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The categories of this paper are: alg-geom
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The categories of this paper are: econ
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The categories of this paper are: math
4
The categories of this paper are: cond-mat
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The categories of this paper are: solv-int
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The categories of this paper are: dg-ga
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The categories of this paper are: math-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: hep-ph
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The categories of this paper are: gr-qc
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The categories of this paper are: chem-ph
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The categories of this paper are: hep-th