Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Winter Road Surface Condition Recognition Using A Pretrained Deep
  Convolutional Network   This paper investigates the application of the latest machine learning
technique deep neural networks for classifying road surface conditions (RSC)
based on images from smartphones. Traditional machine learning techniques such
as support vector machine (SVM) and random forests (RF) have been attempted in
literature; however, their classification performance has been less than
desirable due to challenges associated with image noises caused by sunlight
glare and residual salts. A deep learning model based on convolutional neural
network (CNN) is proposed and evaluated for its potential to address these
challenges for improved classification accuracy. In the proposed approach we
introduce the idea of applying an existing CNN model that has been pre-trained
using millions of images with proven high recognition accuracy. The model is
extended with two additional fully-connected layers of neurons for learning the
specific features of the RSC images. The whole model is then trained with a low
learning rate for fine-tuning by using a small set of RSC images. Results show
that the proposed model has the highest classification performance in
comparison to the traditional machine learning techniques. The testing accuracy
with different training dataset sizes is also analyzed, showing the potential
of achieving much higher accuracy with a larger training dataset.

14
The categories of this paper are: math-ph
28
The categories of this paper are: alg-geom
6
The categories of this paper are: astro-ph
11
The categories of this paper are: hep-lat
16
The categories of this paper are: stat
37
The categories of this paper are: supr-con
15
The categories of this paper are: nucl-ex
2
The categories of this paper are: math
35
The categories of this paper are: mtrl-th
36
The categories of this paper are: cmp-lg
4
The categories of this paper are: cond-mat
13
The categories of this paper are: quant-ph
12
The categories of this paper are: nucl-th
34
The categories of this paper are: chem-ph
9
The categories of this paper are: nlin
31
The categories of this paper are: ao-sci