Testing a New Ensemble Vegetation Classification Method Based on Deep Learning and Machine Learning Methods Using Aerial Photogrammetric Images
The objective of this research is to report results from a new ensemble method for vegetation classification that uses deep learning (DL) and machine learning (ML) techniques. Deep learning and machine learning architectures have recently been used in methods for vegetation classification, proving t...
Main Authors: | Siniša Drobnjak, Marko Stojanović, Dejan Djordjević, Saša Bakrač, Jasmina Jovanović, Aleksandar Djordjević |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2022-05-01
|
Series: | Frontiers in Environmental Science |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fenvs.2022.896158/full |
Similar Items
-
Using historical aerial photography for monitoring of environment changes: a case study of Bovan Lake, Eastern Serbia
by: Saša Bakrač, et al.
Published: (2021-10-01) -
Application of machine learning methods in the classification of satellite images
by: Čurlin Martina T., et al.
Published: (2024-01-01) -
Using Historical Aerial Photography in Landslide Monitoring: Umka Case Study, Serbia
by: Dejan Radovan Đorđević, et al.
Published: (2022-12-01) -
Processing of data collected by unmanned aerial photogrammetry systems
by: Stanojković Vujadin G., et al.
Published: (2022-01-01) -
Subsurface drainage pipe detection using an ensemble learning approach and aerial images
by: Dong Kook Woo, et al.
Published: (2023-09-01)