Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Robotic Detection of Marine Litter Using Deep Visual Detection Models   Trash deposits in aquatic environments have a destructive effect on marine
ecosystems and pose a long-term economic and environmental threat. Autonomous
underwater vehicles (AUVs) could very well contribute to the solution of this
problem by finding and eventually removing trash. This paper evaluates a number
of deep-learning algorithms preforming the task of visually detecting trash in
realistic underwater environments, with the eventual goal of exploration,
mapping, and extraction of such debris by using AUVs. A large and
publicly-available dataset of actual debris in open-water locations is
annotated for training a number of convolutional neural network architectures
for object detection. The trained networks are then evaluated on a set of
images from other portions of that dataset, providing insight into approaches
for developing the detection capabilities of an AUV for underwater trash
removal. In addition, the evaluation is performed on three different platforms
of varying processing power, which serves to assess these algorithms' fitness
for real-time applications.

7
The categories of this paper are: hep-th
16
The categories of this paper are: stat
11
The categories of this paper are: hep-lat
35
The categories of this paper are: mtrl-th
19
The categories of this paper are: eess
20
The categories of this paper are: acc-phys
37
The categories of this paper are: supr-con
23
The categories of this paper are: solv-int
33
The categories of this paper are: plasm-ph
10
The categories of this paper are: q-bio
12
The categories of this paper are: nucl-th
13
The categories of this paper are: quant-ph
22
The categories of this paper are: chao-dyn
14
The categories of this paper are: math-ph
17
The categories of this paper are: q-fin
0
The categories of this paper are: hep-ph