Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep Learning based Automated Forest Health Diagnosis from Aerial Images   Global climate change has had a drastic impact on our environment. Previous
study showed that pest disaster occured from global climate change may cause a
tremendous number of trees died and they inevitably became a factor of forest
fire. An important portent of the forest fire is the condition of forests.
Aerial image-based forest analysis can give an early detection of dead trees
and living trees. In this paper, we applied a synthetic method to enlarge
imagery dataset and present a new framework for automated dead tree detection
from aerial images using a re-trained Mask RCNN (Mask Region-based
Convolutional Neural Network) approach, with a transfer learning scheme. We
apply our framework to our aerial imagery datasets,and compare eight fine-tuned
models. The mean average precision score (mAP) for the best of these models
reaches 54%. Following the automated detection, we are able to automatically
produce and calculate number of dead tree masks to label the dead trees in an
image, as an indicator of forest health that could be linked to the causal
analysis of environmental changes and the predictive likelihood of forest fire.

22
The categories of this paper are: chao-dyn
8
The categories of this paper are: hep-ex
11
The categories of this paper are: hep-lat
2
The categories of this paper are: math
4
The categories of this paper are: cond-mat
33
The categories of this paper are: plasm-ph
19
The categories of this paper are: eess
9
The categories of this paper are: nlin
6
The categories of this paper are: astro-ph
28
The categories of this paper are: alg-geom
16
The categories of this paper are: stat
15
The categories of this paper are: nucl-ex
31
The categories of this paper are: ao-sci
27
The categories of this paper are: comp-gas
13
The categories of this paper are: quant-ph
24
The categories of this paper are: dg-ga