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Ditemukan 23 dari pencarian Anda melalui kata kunci: subject="Segmentation"
Hal. Awal Sebelumnya 1 2 3
cover
Semantic segmentation of point cloud data using raw laser scanner measurement…
Komentar Bagikan
Antero KukkoHarri KaartinenAimad El IssaouiRisto KaijaluotoJuha Hyyppa

Deep learning methods based on convolutional neural networks have shown to give excellent results in semantic segmentation of images, but the inherent irregularity of point cloud data complicates their usage in semantically segmenting 3D laser scanning data. To overcome this problem, point cloud networks particularly specialized for the purpose have been implemented since 2017 but finding the m…

Edisi
Vol.3, January 2022
ISBN/ISSN
1872-8235
Deskripsi Fisik
16 hlm PDF, 8.371 KB
Judul Seri
ISPRS Open Journal of Photogrammetry and Remote Sensing
No. Panggil
621.3678
cover
Deep learning approach for Sentinel-1 surface water mapping leveraging
Komentar Bagikan
Ate PoortingaNyein Soe ThwalTimothy MayerBiplov BhandariKel MarkertAndrea P. NicolauNicholas ClintonDavid SaahAmanda MarkertArjen HaagJohn KilbrideFarrukh ChishtieAmit Wadhwa

Satellite remote sensing plays an important role in mapping the location and extent of surface water. A variety of approaches are available for mapping surface water, but deep learning approaches are not commonplace as they are ‘data hungry’ and require large amounts of computational resources. However, with the availability of various satellite sensors and rapid development in cloud comput…

Edisi
Vol.2, December 2021
ISBN/ISSN
1872-8235
Deskripsi Fisik
13 hlm PDF, 4.033 KB
Judul Seri
ISPRS Open Journal of Photogrammetry and Remote Sensing
No. Panggil
621.3678
cover
The Hessigheim 3D (H3D) benchmark on semantic segmentation of high-resolution…
Komentar Bagikan
Michael KolleDominik LaupheimerStefan SchmohlNorbert HaalaFranz RottensteinerJan Dirk WegnerHugo Ledoux

Automated semantic segmentation and object detection are of great importance in geospatial data analysis. However, supervised machine learning systems such as convolutional neural networks require large corpora of annotated training data. Especially in the geospatial domain, such datasets are quite scarce. Within this paper, we aim to alleviate this issue by introducing a new annotated 3D datas…

Edisi
Vol.1, October 2021
ISBN/ISSN
1872-8235
Deskripsi Fisik
11 hlm PDF., 8,202 KB
Judul Seri
ISPRS Open Journal of Photogrammetry and Remote Sensing
No. Panggil
621.3678
Hal. Awal Sebelumnya 1 2 3