Ensemble of Deep Learning-Based Multimodal Remote Sensing Image Classification Model on Unmanned Aerial Vehicle Networks
Recently, unmanned aerial vehicles (UAVs) have been used in several applications of environmental modeling and land use inventories. At the same time, the computer vision-based remote sensing image classification models are needed to monitor the modifications over time such as vegetation, inland wat...
Saved in:
Main Authors: | Gyanendra Prasad Joshi, Fayadh Alenezi, Gopalakrishnan Thirumoorthy, Ashit Kumar Dutta, Jinsang You |
---|---|
Format: | article |
Language: | EN |
Published: |
MDPI AG
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/3d9928f159ef440f83a947f0d8e9eb63 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Estimation of aboveground biomass using aerial photogrammetry from unmanned aerial vehicle in teak (Tectona grandis) plantation in Thailand
by: SASIWIMOL RINNAMANG, et al.
Published: (2020) -
Assessing Grapevine Nutrient Status from Unmanned Aerial System (UAS) Hyperspectral Imagery
by: Robert Chancia, et al.
Published: (2021) -
A Survey of Cyberattack Countermeasures for Unmanned Aerial Vehicles
by: Peng-Yong Kong
Published: (2021) -
Event-Triggered Formation Tracking Control for Unmanned Aerial Vehicles Subjected to Deception Attacks
by: Biao Sun, et al.
Published: (2021) -
Unmanned aerial vehicle evasion manoeuvres from enemy aircraft attack
by: Evdokimenkov Veniamin N., et al.
Published: (2021)