Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Incremental Learning in Deep Convolutional Neural Networks Using Partial
  Network Sharing   Deep convolutional neural network (DCNN) based supervised learning is a
widely practiced approach for large-scale image classification. However,
retraining these large networks to accommodate new, previously unseen data
demands high computational time and energy requirements. Also, previously seen
training samples may not be available at the time of retraining. We propose an
efficient training methodology and incrementally growing DCNN to learn new
tasks while sharing part of the base network. Our proposed methodology is
inspired by transfer learning techniques, although it does not forget
previously learned tasks. An updated network for learning new set of classes is
formed using previously learned convolutional layers (shared from initial part
of base network) with addition of few newly added convolutional kernels
included in the later layers of the network. We employed a `clone-and-branch'
technique which allows the network to learn new tasks one after another without
any performance loss in old tasks. We evaluated the proposed scheme on several
recognition applications. The classification accuracy achieved by our approach
is comparable to the regular incremental learning approach (where networks are
updated with new training samples only, without any network sharing), while
achieving energy efficiency, reduction in storage requirements, memory access
and training time.

3
The categories of this paper are: physics
30
The categories of this paper are: q-alg
28
The categories of this paper are: alg-geom
4
The categories of this paper are: cond-mat
5
The categories of this paper are: gr-qc
26
The categories of this paper are: bayes-an
14
The categories of this paper are: math-ph
16
The categories of this paper are: stat
19
The categories of this paper are: eess
29
The categories of this paper are: funct-an
12
The categories of this paper are: nucl-th
11
The categories of this paper are: hep-lat
23
The categories of this paper are: solv-int
17
The categories of this paper are: q-fin
0
The categories of this paper are: hep-ph
18
The categories of this paper are: econ