Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Robust Semi-supervised Federated Learning for Images Automatic
  Recognition in Internet of Drones   Air access networks have been recognized as a significant driver of various
Internet of Things (IoT) services and applications. In particular, the aerial
computing network infrastructure centered on the Internet of Drones has set off
a new revolution in automatic image recognition. This emerging technology
relies on sharing ground truth labeled data between Unmanned Aerial Vehicle
(UAV) swarms to train a high-quality automatic image recognition model.
However, such an approach will bring data privacy and data availability
challenges. To address these issues, we first present a Semi-supervised
Federated Learning (SSFL) framework for privacy-preserving UAV image
recognition. Specifically, we propose model parameters mixing strategy to
improve the naive combination of FL and semi-supervised learning methods under
two realistic scenarios (labels-at-client and labels-at-server), which is
referred to as Federated Mixing (FedMix). Furthermore, there are significant
differences in the number, features, and distribution of local data collected
by UAVs using different camera modules in different environments, i.e.,
statistical heterogeneity. To alleviate the statistical heterogeneity problem,
we propose an aggregation rule based on the frequency of the client's
participation in training, namely the FedFreq aggregation rule, which can
adjust the weight of the corresponding local model according to its frequency.
Numerical results demonstrate that the performance of our proposed method is
significantly better than those of the current baseline and is robust to
different non-IID levels of client data.

25
The categories of this paper are: patt-sol
33
The categories of this paper are: plasm-ph
6
The categories of this paper are: astro-ph
30
The categories of this paper are: q-alg
14
The categories of this paper are: math-ph
29
The categories of this paper are: funct-an
8
The categories of this paper are: hep-ex
24
The categories of this paper are: dg-ga
37
The categories of this paper are: supr-con
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
35
The categories of this paper are: mtrl-th
3
The categories of this paper are: physics
21
The categories of this paper are: adap-org
28
The categories of this paper are: alg-geom