Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Hardware based Spatio-Temporal Neural Processing Backend for Imaging
  Sensors: Towards a Smart Camera   In this work we show how we can build a technology platform for cognitive
imaging sensors using recent advances in recurrent neural network architectures
and training methods inspired from biology. We demonstrate learning and
processing tasks specific to imaging sensors, including enhancement of
sensitivity and signal-to-noise ratio (SNR) purely through neural filtering
beyond the fundamental limits sensor materials, and inferencing and
spatio-temporal pattern recognition capabilities of these networks with
applications in object detection, motion tracking and prediction. We then show
designs of unit hardware cells built using complementary metal-oxide
semiconductor (CMOS) and emerging materials technologies for ultra-compact and
energy-efficient embedded neural processors for smart cameras.

35
The categories of this paper are: mtrl-th
5
The categories of this paper are: gr-qc
17
The categories of this paper are: q-fin
34
The categories of this paper are: chem-ph
0
The categories of this paper are: hep-ph
7
The categories of this paper are: hep-th
32
The categories of this paper are: atom-ph
27
The categories of this paper are: comp-gas
26
The categories of this paper are: bayes-an
36
The categories of this paper are: cmp-lg
8
The categories of this paper are: hep-ex
29
The categories of this paper are: funct-an
13
The categories of this paper are: quant-ph
31
The categories of this paper are: ao-sci
28
The categories of this paper are: alg-geom
2
The categories of this paper are: math