Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deploying Deep Neural Networks in the Embedded Space   Recently, Deep Neural Networks (DNNs) have emerged as the dominant model
across various AI applications. In the era of IoT and mobile systems, the
efficient deployment of DNNs on embedded platforms is vital to enable the
development of intelligent applications. This paper summarises our recent work
on the optimised mapping of DNNs on embedded settings. By covering such diverse
topics as DNN-to-accelerator toolflows, high-throughput cascaded classifiers
and domain-specific model design, the presented set of works aim to enable the
deployment of sophisticated deep learning models on cutting-edge mobile and
embedded systems.

28
The categories of this paper are: alg-geom
36
The categories of this paper are: cmp-lg
0
The categories of this paper are: hep-ph
29
The categories of this paper are: funct-an
23
The categories of this paper are: solv-int
7
The categories of this paper are: hep-th
33
The categories of this paper are: plasm-ph
30
The categories of this paper are: q-alg
32
The categories of this paper are: atom-ph
27
The categories of this paper are: comp-gas
15
The categories of this paper are: nucl-ex
8
The categories of this paper are: hep-ex
10
The categories of this paper are: q-bio
11
The categories of this paper are: hep-lat
13
The categories of this paper are: quant-ph
22
The categories of this paper are: chao-dyn