Deforestation detection using deep learning-based semantic segmentation techniques: a systematic review
Deforestation poses a critical global threat to Earth’s ecosystem and biodiversity, necessitating effective monitoring and mitigation strategies. The integration of deep learning with remote sensing offers a promising solution for precise deforestation segmentation and detection. This paper provides...
Published in: | Frontiers in Forests and Global Change |
---|---|
Main Author: | Md Jelas I.; Zulkifley M.A.; Abdullah M.; Spraggon M. |
Format: | Review |
Language: | English |
Published: |
Frontiers Media SA
2024
|
Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185502301&doi=10.3389%2fffgc.2024.1300060&partnerID=40&md5=e723e24477e4361c77098bccf0f655f8 |
Similar Items
-
Deforestation detection using deep learning-based semantic segmentation techniques: a systematic review
by: Jelas, et al.
Published: (2024) -
Attention-Based Semantic Segmentation Networks for Forest Applications
by: Lim S.V.; Zulkifley M.A.; Saleh A.; Saputro A.H.; Abdani S.R.
Published: (2023) -
Research on Deep Learning-based Semantic Segmentation Algorithm for UAV Images
by: Yan Q.; Cheng G.
Published: (2023) -
Attention-Based Semantic Segmentation Networks for Forest Applications
by: Lim, et al.
Published: (2023) -
Rumor detection based on deep learning techniques: a systematic review
by: Zhang L.; Ibrahim S.; Fadzil A.F.A.
Published: (2024)