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Ditemukan 4 dari pencarian Anda melalui kata kunci: author=Juha Hyyppa
cover
Individual tree segmentation and species classification using high-density cl…
Komentar Bagikan
Eric HyyppaXiaowei YuAntero KukkoHarri KaartinenMatti LehtomakiJuha HyyppaLeena MatikainenMarkus HolopainenAada HakulaLassi RuoppaJosef TaherVille LuomaVille Kankare

Tree species characterise biodiversity, health, economic potential, and resilience of an ecosystem, for example. Tree species classification based on remote sensing data, however, is known to be a challenging task. In this paper, we study for the first time the feasibility of tree species classification using high-density point clouds collected with an airborne close-range multispectral laser s…

Edisi
Vol.9, August 2023
ISBN/ISSN
1872-8235
Deskripsi Fisik
15 hlm PDF, 2.550 KB
Judul Seri
ISPRS Open Journal of Photogrammetry and Remote Sensing
No. Panggil
621.3678
cover
Branch information extraction from Norway spruce using handheld laser scannin…
Komentar Bagikan
Xiaowei YuAntero KukkoHarri KaartinenMatti LehtomakiJuha HyyppaOlli WinbergJiri PyoralaMarkus HolopainenJohan Holmgren

We showed that a mobile handheld laser scanner (HHLS) provides useful features concerning the wood quality-influencing external structures of trees. When linked with wood properties measured at a sawmill utilizing state-of-the-art X-ray scanners, these data enable the training of various wood quality models for use in targeting and planning future wood procurement. A total of 457 Norway spruce …

Edisi
Vol.9, August 2023
ISBN/ISSN
1872-8235
Deskripsi Fisik
15 hlm PDF, 10.203 PDF
Judul Seri
ISPRS Open Journal of Photogrammetry and Remote Sensing
No. Panggil
621.3678
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
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