Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep Joint Source-Channel Coding for Wireless Image Retrieval   Motivated by surveillance applications with wireless cameras or drones, we
consider the problem of image retrieval over a wireless channel. Conventional
systems apply lossy compression on query images to reduce the data that must be
transmitted over the bandwidth and power limited wireless link. We first note
that reconstructing the original image is not needed for retrieval tasks;
hence, we introduce a deep neutral network (DNN) based compression scheme
targeting the retrieval task. Then, we completely remove the compression step,
and propose another DNN-based communication scheme that directly maps the
feature vectors to channel inputs. This joint source-channel coding (JSCC)
approach not only improves the end-to-end accuracy, but also simplifies and
speeds up the encoding operation which is highly beneficial for power and
latency constrained IoT applications.

16
The categories of this paper are: stat
35
The categories of this paper are: mtrl-th
25
The categories of this paper are: patt-sol
36
The categories of this paper are: cmp-lg
26
The categories of this paper are: bayes-an
21
The categories of this paper are: adap-org
12
The categories of this paper are: nucl-th
20
The categories of this paper are: acc-phys
33
The categories of this paper are: plasm-ph
15
The categories of this paper are: nucl-ex
11
The categories of this paper are: hep-lat
8
The categories of this paper are: hep-ex
28
The categories of this paper are: alg-geom
5
The categories of this paper are: gr-qc
17
The categories of this paper are: q-fin
9
The categories of this paper are: nlin