Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Scalable Neural Architecture Search for 3D Medical Image Segmentation   In this paper, a neural architecture search (NAS) framework is proposed for
3D medical image segmentation, to automatically optimize a neural architecture
from a large design space. Our NAS framework searches the structure of each
layer including neural connectivities and operation types in both of the
encoder and decoder. Since optimizing over a large discrete architecture space
is difficult due to high-resolution 3D medical images, a novel stochastic
sampling algorithm based on a continuous relaxation is also proposed for
scalable gradient based optimization. On the 3D medical image segmentation
tasks with a benchmark dataset, an automatically designed architecture by the
proposed NAS framework outperforms the human-designed 3D U-Net, and moreover
this optimized architecture is well suited to be transferred for different
tasks.

15
The categories of this paper are: nucl-ex
27
The categories of this paper are: comp-gas
3
The categories of this paper are: physics
34
The categories of this paper are: chem-ph
8
The categories of this paper are: hep-ex
26
The categories of this paper are: bayes-an
23
The categories of this paper are: solv-int
30
The categories of this paper are: q-alg
20
The categories of this paper are: acc-phys
10
The categories of this paper are: q-bio
28
The categories of this paper are: alg-geom
33
The categories of this paper are: plasm-ph
4
The categories of this paper are: cond-mat
17
The categories of this paper are: q-fin
11
The categories of this paper are: hep-lat
36
The categories of this paper are: cmp-lg