Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Comprehensive Semantic Segmentation on High Resolution UAV Imagery for
  Natural Disaster Damage Assessment   In this paper, we present a large-scale hurricane Michael dataset for visual
perception in disaster scenarios, and analyze state-of-the-art deep neural
network models for semantic segmentation. The dataset consists of around 2000
high-resolution aerial images, with annotated ground-truth data for semantic
segmentation. We discuss the challenges of the dataset and train the
state-of-the-art methods on this dataset to evaluate how well these methods can
recognize the disaster situations. Finally, we discuss challenges for future
research.

5
The categories of this paper are: gr-qc
36
The categories of this paper are: cmp-lg
24
The categories of this paper are: dg-ga
23
The categories of this paper are: solv-int
27
The categories of this paper are: comp-gas
3
The categories of this paper are: physics
25
The categories of this paper are: patt-sol
35
The categories of this paper are: mtrl-th
32
The categories of this paper are: atom-ph
8
The categories of this paper are: hep-ex
22
The categories of this paper are: chao-dyn
19
The categories of this paper are: eess
30
The categories of this paper are: q-alg
37
The categories of this paper are: supr-con
12
The categories of this paper are: nucl-th
9
The categories of this paper are: nlin