People Detection Using Artificial Intelligence with Panchromatic Satellite Images

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F24%3A10255675" target="_blank" >RIV/61989100:27240/24:10255675 - isvavai.cz</a>

Alternative codes found

RIV/61989100:27350/24:10255675

Result on the web

<a href="https://www.mdpi.com/2076-3417/14/18/8555" target="_blank" >https://www.mdpi.com/2076-3417/14/18/8555</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/app14188555" target="_blank" >10.3390/app14188555</a>

Result language

angličtina

Original language name

People Detection Using Artificial Intelligence with Panchromatic Satellite Images

Original language description

The detection of people in urban environments from satellite imagery can be employed in a variety of applications, such as urban planning, business management, crisis management, military operations, and security. A WorldView-3 satellite image of Prague was processed. Several variants of feature-extracting networks, referred to as backbone networks, were tested alongside the Faster R-CNN model. This model combines region proposal networks with object detection, offering a balance between speed and accuracy that is well suited for dense and varied urban environments. Data augmentation was used to increase the robustness of the models, which contributed to the improvement of classification results. Achieving a high level of accuracy is an ongoing challenge due to the low spatial resolution of available imagery. An F1 score of 54% was achieved using data augmentation, a 15 cm buffer, and a maximum distance limit of 60 cm. (C) 2024 by the authors.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10500 - Earth and related environmental sciences

Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Applied Sciences

ISSN

2076-3417

e-ISSN

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Volume of the periodical

14

Issue of the periodical within the volume

18

Country of publishing house

CH - SWITZERLAND

Number of pages

16

Pages from-to

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UT code for WoS article

001323310900001

EID of the result in the Scopus database

2-s2.0-85205293744