Ditapis dengan
Monitoring aseismic fault creep using persistent urban geodetic markers gener…
High resolution and high accuracy distributed detection of fault creep deformation remains challenging given limited observations and associated change detection strategies. A mobile laser scanning-based change detection method that is capable of measuring centimeter-level near-field ( m from fault) deformation is described. The methodology leverages the use of man-made features in the built …
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 12 hlm PDF, 6.019 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Efficient coarse registration method using translation- and rotation-invarian…
In this paper, we present a simple, efficient, and robust algorithm for 2D coarse registration of two point clouds. In the proposed algorithm, the locations of some distinct objects are detected from the point cloud data, and a rotation- and translation-invariant feature descriptor vector is computed for each of the detected objects based on the relative locations of the neighboring objects. Su…
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 16 hlm PDF, 4.155 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Towards spherical robots for mobile mapping in human made environments
Spherical robots are a format that has not been thoroughly explored for the application of mobile mapping. In contrast to other designs, it provides some unique advantages. Among those is a spherical shell that protects internal sensors and actuators from possible harsh environments, as well as an inherent rotation for locomotion that enables measurements in all directions. Mobile mapping alway…
- Edisi
- Vol.1, October 2021
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 13 hlm PDF, 9,142 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
The Hessigheim 3D (H3D) benchmark on semantic segmentation of high-resolution…
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
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