Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: FusionNet: A deep fully residual convolutional neural network for image
  segmentation in connectomics   Electron microscopic connectomics is an ambitious research direction with the
goal of studying comprehensive brain connectivity maps by using
high-throughput, nano-scale microscopy. One of the main challenges in
connectomics research is developing scalable image analysis algorithms that
require minimal user intervention. Recently, deep learning has drawn much
attention in computer vision because of its exceptional performance in image
classification tasks. For this reason, its application to connectomic analyses
holds great promise, as well. In this paper, we introduce a novel deep neural
network architecture, FusionNet, for the automatic segmentation of neuronal
structures in connectomics data. FusionNet leverages the latest advances in
machine learning, such as semantic segmentation and residual neural networks,
with the novel introduction of summation-based skip connections to allow a much
deeper network architecture for a more accurate segmentation. We demonstrate
the performance of the proposed method by comparing it with state-of-the-art
electron microscopy (EM) segmentation methods from the ISBI EM segmentation
challenge. We also show the segmentation results on two different tasks
including cell membrane and cell body segmentation and a statistical analysis
of cell morphology.

30
The categories of this paper are: q-alg
9
The categories of this paper are: nlin
10
The categories of this paper are: q-bio
7
The categories of this paper are: hep-th
27
The categories of this paper are: comp-gas
29
The categories of this paper are: funct-an
26
The categories of this paper are: bayes-an
23
The categories of this paper are: solv-int
21
The categories of this paper are: adap-org
2
The categories of this paper are: math
3
The categories of this paper are: physics
24
The categories of this paper are: dg-ga
34
The categories of this paper are: chem-ph
20
The categories of this paper are: acc-phys
37
The categories of this paper are: supr-con
16
The categories of this paper are: stat