Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Pseudo Rehearsal using non photo-realistic images   Deep Neural networks forget previously learnt tasks when they are faced with
learning new tasks. This is called catastrophic forgetting. Rehearsing the
neural network with the training data of the previous task can protect the
network from catastrophic forgetting. Since rehearsing requires the storage of
entire previous data, Pseudo rehearsal was proposed, where samples belonging to
the previous data are generated synthetically for rehearsal. In an image
classification setting, while current techniques try to generate synthetic data
that is photo-realistic, we demonstrated that Neural networks can be rehearsed
on data that is not photo-realistic and still achieve good retention of the
previous task. We also demonstrated that forgoing the constraint of having
photo realism in the generated data can result in a significant reduction in
the consumption of computational and memory resources for pseudo rehearsal.

8
The categories of this paper are: hep-ex
11
The categories of this paper are: hep-lat
18
The categories of this paper are: econ
34
The categories of this paper are: chem-ph
30
The categories of this paper are: q-alg
4
The categories of this paper are: cond-mat
37
The categories of this paper are: supr-con
27
The categories of this paper are: comp-gas
29
The categories of this paper are: funct-an
2
The categories of this paper are: math
36
The categories of this paper are: cmp-lg
23
The categories of this paper are: solv-int
7
The categories of this paper are: hep-th
24
The categories of this paper are: dg-ga
19
The categories of this paper are: eess
33
The categories of this paper are: plasm-ph