Ditapis dengan
Irregularly sampled seismic data interpolation via wavelet-based convolutiona…
Seismic data interpolation, especially irregularly sampled data interpolation, is a critical task for seismic processing and subsequent interpretation. Recently, with the development of machine learning and deep learning, convolutional neural networks (CNNs) are applied for interpolating irregularly sampled seismic data. CNN based approaches can address the apparent defects of traditional inter…
- Edisi
- Vol.3, December 2022
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 11 hlm PDF, 5.141 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Reconstruction of reservoir rock using attention-based convolutional recurren…
The digital reconstruction of reservoir rock or porous media is important as it enables us to visualize and explore their real internal structures. The reservoir rocks (such as sandstone and carbonate) contain both spatial and temporal characteristics, which pose a big challenge in their characterization through routine core analysis or x-ray microcomputer tomography. While x-ray micro-computed…
- Edisi
- Vol.24, December 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 18 hlm PDF, 14.609 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Compaction trend estimation and applications to sedimentary basin reconstruct…
BasinVis 1.0, a MATLAB-based modular open-source program released in 2016, has been used for multiple application studies of sedimentary basin analysis and modelling in both academic and industry fields. Based on these studies and user feedbacks, we have improved the workflow, revised user interfaces and developed novel techniques for the compaction trend estimation of infilling sediments and i…
- Edisi
- Vol.5, March 2020
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 12 hlm PDF, 4.654 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
UseGeo - A UAV-based multi-sensor dataset for geospatial research
3D reconstruction is a long-standing research topic in the photogrammetric and computer vision communities; although a plethora of open-source and commercial solutions for 3D reconstruction have been released in the last few years, several open challenges and limitations still exist. Undoubtedly, deep learning algorithms have demonstrated great potential in several remote sensing tasks, includi…
- Edisi
- Vol.13, August 2024
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 12 hlm PDF, 7.935 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Depth estimation and 3D reconstruction from UAV-borne imagery: Evaluation on …
Depth estimation and 3D model reconstruction from aerial imagery is an important task in photogrammetry, remote sensing, and computer vision. To compare the performance of different image-based approaches, this study presents a benchmark for UAV-based aerial imagery using the UseGeo dataset. The contributions include the release of various evaluation routines on GitHub, as well as a comprehensi…
- Edisi
- Vol.13, August 2024
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 20 hlm PDF, 25.233 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Results of the ISPRS benchmark on indoor modelling
This paper reports the results of the ISPRS benchmark on indoor modelling. Reconstructed models submitted by 11 participating teams are evaluated on a dataset comprising 6 point clouds representing indoor environments of different complexity. The evaluation is based on measuring the completeness, correctness, and accuracy of the reconstructed wall elements through comparison with manually gener…
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 13 hlm PDF, 4.462 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
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