Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Bio-Measurements Estimation and Support in Knee Recovery through Machine
  Learning   Knee injuries are frequent, varied and often require the patient to undergo
intensive rehabilitation for several months. Treatment protocols usually
contemplate some recurrent measurements in order to assess progress, such as
goniometry. The need for specific equipment or the complexity and duration of
these tasks cause them to often be neglected. A novel deep learning based
solution is presented, supported by the generation of a synthetic image
dataset. A 3D human-body model was used for this purpose, simulating a
recovering patient. For each image, the coordinates of three key points were
registered: the centers of the thigh, the knee and the lower leg. These values
are sufficient to estimate the flexion angle. Convolutional neural networks
were then trained for predicting these six coordinates. Transfer learning was
used with the VGG16 and InceptionV3 models pre-trained on the ImageNet dataset,
being an additional custom model trained from scratch. All models were tested
with different combinations of data augmentation techniques applied on the
training sets. InceptionV3 achieved the best overall results, producing
considerably good predictions even on real unedited pictures.

16
The categories of this paper are: stat
24
The categories of this paper are: dg-ga
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The categories of this paper are: nucl-ex
4
The categories of this paper are: cond-mat
6
The categories of this paper are: astro-ph
31
The categories of this paper are: ao-sci
18
The categories of this paper are: econ
26
The categories of this paper are: bayes-an
34
The categories of this paper are: chem-ph
0
The categories of this paper are: hep-ph
23
The categories of this paper are: solv-int
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The categories of this paper are: math-ph
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The categories of this paper are: hep-lat
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The categories of this paper are: nlin
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The categories of this paper are: q-fin
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The categories of this paper are: nucl-th