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Ditemukan 5 dari pencarian Anda melalui kata kunci: subject="Change detection"
cover
Land use and land cover classification for change detection studies using con…
Komentar Bagikan
V. PushpalathaP.B. MallikarjunaH.N. MahendraS. Rama SubramoniamS. Mallikarjunaswamy

Efficient land use land cover (LULC) classification is crucial for environmental monitoring, urban planning, and resource management. This study investigates LULC changes in Nanjangud taluk, Mysuru district, Karnataka, India, using remote sensing (RS) and geographic information systems (GIS). This paper mainly focuses on the classification and change detection analysis of LULC in 2010 and 2020 …

Edisi
Vol.25, February 2025
ISBN/ISSN
2590-1974
Deskripsi Fisik
17 hlm PDF, 11.125 KB
Judul Seri
Applied Computing and Geoscience - Open Access
No. Panggil
551.136
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
cover
An UNet3+ Network based on global pyramid aggregation for change detection in…
Komentar Bagikan
Yanbo SunWenxing BaoWei FengKewen QuXuan MaaXiaowu Zhang

Change detection (CD) is a meaningful and challenging task for remote sensing (RS) image analysis. Deep learning (DL) based methods have shown great potential in change detection tasks, there are still two problems with existing deep learning methods such as CNN and Transformer: (1) They do not target different depths to extract global semantics in the network; (2) The increase in network depth…

Edisi
Vol.24, December 2024
ISBN/ISSN
2590-1974
Deskripsi Fisik
14 hlm PDF, 4.185 KB
Judul Seri
Applied Computing and Geoscience - Open Access
No. Panggil
551.136
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
cover
Deep unsupervised learning for 3D ALS point clouds change detection
Komentar Bagikan
Iris de GelisSudipan SahaMuhammad ShahzadThomas CorpettiSebastien LefevreXiao Xiang Zhu

Change detection from traditional 2D optical images has limited capability to model the changes in the height or shape of objects. Change detection using 3D point cloud from photogrammetry or LiDAR surveying can fill this gap by providing critical depth information. While most existing machine learning based 3D point cloud change detection methods are supervised, they severely depend on the ava…

Edisi
Vol.9, August 2023
ISBN/ISSN
1872-8235
Deskripsi Fisik
11 hlm PDF, 11.265 KB
Judul Seri
ISPRS Open Journal of Photogrammetry and Remote Sensing
No. Panggil
621.3678
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
cover
Automatic labelling for semantic segmentation of VHR satellite images: Applic…
Komentar Bagikan
Juha HyyppaKirsi KarilaLeena MatikainenMika KarjalainenEetu PuttonenYuwei Chen

The application of deep learning methods to remote sensing data has produced good results in recent studies. A promising application area is automatic land cover classification (semantic segmentation) from very high-resolution satellite imagery. However, the deep learning methods require large, labelled training datasets that are suitable for the study area. Map data can be used as training dat…

Edisi
Vol.9, August 2023
ISBN/ISSN
1872-8235
Deskripsi Fisik
11 hlm PDF, 15.060 KB
Judul Seri
ISPRS Open Journal of Photogrammetry and Remote Sensing
No. Panggil
621.3678
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
cover
Change detection in street environments based on mobile laser scanning: A fuz…
Komentar Bagikan
Joachim GehrungMarcus HebelMichael ArensUwe Stilla

Automated change detection based on urban mobile laser scanning data is the foundation for a whole range of applications such as building model updates, map generation for autonomous driving and natural disaster assessment. The challenge with mobile LiDAR data is that various sources of error, such as localization errors, lead to uncertainties and contradictions in the derived information. This…

Edisi
Vol.5, August 2022
ISBN/ISSN
1872-8235
Deskripsi Fisik
17 hlm PDF, 18,263 KB
Judul Seri
ISPRS Open Journal of Photogrammetry and Remote Sensing
No. Panggil
621.3678
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
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