Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Segmentation of Surgical Instruments for Minimally-Invasive
  Robot-Assisted Procedures Using Generative Deep Neural Networks   This work proves that semantic segmentation on minimally invasive surgical
instruments can be improved by using training data that has been augmented
through domain adaptation. The benefit of this method is twofold. Firstly, it
suppresses the need of manually labeling thousands of images by transforming
synthetic data into realistic-looking data. To achieve this, a CycleGAN model
is used, which transforms a source dataset to approximate the domain
distribution of a target dataset. Secondly, this newly generated data with
perfect labels is utilized to train a semantic segmentation neural network,
U-Net. This method shows generalization capabilities on data with variability
regarding its rotation- position- and lighting conditions. Nevertheless, one of
the caveats of this approach is that the model is unable to generalize well to
other surgical instruments with a different shape from the one used for
training. This is driven by the lack of a high variance in the geometric
distribution of the training data. Future work will focus on making the model
more scale-invariant and able to adapt to other types of surgical instruments
previously unseen by the training.

32
The categories of this paper are: atom-ph
11
The categories of this paper are: hep-lat
5
The categories of this paper are: gr-qc
31
The categories of this paper are: ao-sci
30
The categories of this paper are: q-alg
17
The categories of this paper are: q-fin
8
The categories of this paper are: hep-ex
2
The categories of this paper are: math
35
The categories of this paper are: mtrl-th
37
The categories of this paper are: supr-con
28
The categories of this paper are: alg-geom
20
The categories of this paper are: acc-phys
10
The categories of this paper are: q-bio
4
The categories of this paper are: cond-mat
18
The categories of this paper are: econ
3
The categories of this paper are: physics