Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Is the use of Deep Learning and Artificial Intelligence an appropriate
  means to locate debris in the ocean without harming aquatic wildlife?   With the global issue of plastic debris ever expanding, it is about time that
the technology industry stepped in. This study aims to assess whether deep
learning can successfully distinguish between marine life and man-made debris
underwater. The aim is to find if we are safely able to clean up our oceans
with Artificial Intelligence without disrupting the delicate balance of the
aquatic ecosystems. The research explores the use of Convolutional Neural
Networks from the perspective of protecting the ecosystem, rather than
primarily collecting rubbish. We did this by building a custom-built, deep
learning model, with an original database including 1,644 underwater images and
used a binary classification to sort synthesised material from aquatic life. We
concluded that although it is possible to safely distinguish between debris and
life, further exploration with a larger database and stronger CNN structure has
the potential for much more promising results.

8
The categories of this paper are: hep-ex
16
The categories of this paper are: stat
7
The categories of this paper are: hep-th
3
The categories of this paper are: physics
27
The categories of this paper are: comp-gas
23
The categories of this paper are: solv-int
29
The categories of this paper are: funct-an
9
The categories of this paper are: nlin
35
The categories of this paper are: mtrl-th
36
The categories of this paper are: cmp-lg
5
The categories of this paper are: gr-qc
24
The categories of this paper are: dg-ga
28
The categories of this paper are: alg-geom
10
The categories of this paper are: q-bio
18
The categories of this paper are: econ
21
The categories of this paper are: adap-org