Detail publikace

Aerial Landscape Recognition via Multi-Input Neural Network

KOPEČNÝ, L. HNIDKA, J.

Originální název

Aerial Landscape Recognition via Multi-Input Neural Network

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

Throughout the last decade, the advancements in the hardware allow use for wider applications of the unmanned aerial vehicles (UAV). UAVs feature significant advantages in autonomous aerial landscape mapping and recognition (ALR) over traditional methods due to their high level of operationality and mission repeatability, along with a simple alteration of e.g., on board remote sensors. ALR system based on convolutional neural networks is proposed. The system is designed with real-time capabilities. Data classification based on histogram and Gabor filter is explored on commercially available aerial images. The research roadmap designed to offload the dependency of the process on flight testing to improve the cost-efficiency of the development is proposed as well.

Klíčová slova

aerial landscape recognition; Gabor Filter; histogram; Multi-input neural networks; Principal Component Analysis; Unmanned Aerial Vehicles

Autoři

KOPEČNÝ, L.; HNIDKA, J.

Vydáno

11. 6. 2021

Nakladatel

Institute of Electrical and Electronics Engineers Inc.

ISBN

978-1-6654-3724-0

Kniha

2021 International Conference on Military Technologies (ICMT)

Strany od

1

Strany do

5

Strany počet

5

URL

https://ieeexplore.ieee.org/document/9502749

BibTex

@inproceedings{BUT176844,
  author="Ladislav {Kopečný} and Jakub {Hnidka}",
  title="Aerial Landscape Recognition via Multi-Input Neural Network",
  booktitle="2021 International Conference on Military Technologies (ICMT)",
  year="2021",
  pages="1--5",
  publisher="Institute of Electrical and Electronics Engineers Inc.",
  doi="10.1109/ICMT52455.2021.9502749",
  isbn="978-1-6654-3724-0",
  url="https://ieeexplore.ieee.org/document/9502749"
}