Ditapis dengan
MLReal: Bridging the gap between training on synthetic data and real data app…
Among the biggest challenges we face in utilizing neural networks trained on waveform (i.e., seismic, electromagnetic, or ultrasound) data is its application to real data. The requirement for accurate labels often forces us to train our networks using synthetic data, where labels are readily available. However, synthetic data often fail to capture the reality of the field/real experiment, and w…
- Edisi
- Vol.3, December 2022
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 14 hlm PDF, 3.698 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Generation of CT images from medical CT scans of carbonate rocks using a diff…
Carbonate rocks are known for their high heterogeneity and textural and compositional complexity. Evaluating their petrophysical properties is thus challenging, especially with limited information. One way to obtain an internal image of such rocks is to scan them with X-ray computed tomography scanners, revealing their internal structures. The problem with this approach is the trade-off between…
- Edisi
- Vol.18 June 2023
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 11 hlm PDF, 4.920 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Batas Wilayah 
Ekologi 
Fotogrametri 
Geografi 
Geologi 
GIS 
Ilmu Tanah 
Kartografi 
Manajemen Bencana 
Oceanografi 
Penginderaan Jauh 
Peta