Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: See, Attend and Brake: An Attention-based Saliency Map Prediction Model
  for End-to-End Driving   Visual perception is the most critical input for driving decisions. In this
study, our aim is to understand relationship between saliency and driving
decisions. We present a novel attention-based saliency map prediction model for
making braking decisions This approach constructs a holistic model to the
driving task and can be extended for other driving decisions like steering and
acceleration. The proposed model is a deep neural network model that feeds
extracted features from input image to a recurrent neural network with an
attention mechanism. Then predicted saliency map is used to make braking
decision. We trained and evaluated using driving attention dataset BDD-A, and
saliency dataset CAT2000.

11
The categories of this paper are: hep-lat
4
The categories of this paper are: cond-mat
18
The categories of this paper are: econ
7
The categories of this paper are: hep-th
27
The categories of this paper are: comp-gas
21
The categories of this paper are: adap-org
20
The categories of this paper are: acc-phys
34
The categories of this paper are: chem-ph
31
The categories of this paper are: ao-sci
25
The categories of this paper are: patt-sol
30
The categories of this paper are: q-alg
26
The categories of this paper are: bayes-an
16
The categories of this paper are: stat
29
The categories of this paper are: funct-an
0
The categories of this paper are: hep-ph
35
The categories of this paper are: mtrl-th