| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
Advanced AI techniques for landslide susceptibility mapping and spatial prediction: A case study in Medellín, Colombia
|
Gómez-Miranda, I.N.
|
|
|
25 |
C |
p.
|
artikel
|
| 2 |
A new inversion algorithm (PyMDS) based on the Pyro library to use chlorine 36 data as a paleoseismological tool on normal fault scarps
|
Llinares, Maureen
|
|
|
25 |
C |
p.
|
artikel
|
| 3 |
Automatic variogram inference using pre-trained Convolutional Neural Networks
|
Karim, Mokdad
|
|
|
25 |
C |
p.
|
artikel
|
| 4 |
Chemical map classification in XMapTools
|
Lanari, Pierre
|
|
|
25 |
C |
p.
|
artikel
|
| 5 |
Classification of geological borehole descriptions using a domain adapted large language model
|
Ghorbanfekr, Hossein
|
|
|
25 |
C |
p.
|
artikel
|
| 6 |
Deformation analysis by an improved similarity transformation
|
Mahboub, Vahid
|
|
|
25 |
C |
p.
|
artikel
|
| 7 |
Developing ground motion prediction models for West Java: A machine learning approach to support Indonesia's earthquake early warning system
|
Rachmadan, Andy
|
|
|
25 |
C |
p.
|
artikel
|
| 8 |
Do more with less: Exploring semi-supervised learning for geological image classification
|
Mamode, Hisham I.
|
|
|
25 |
C |
p.
|
artikel
|
| 9 |
Editorial Board
|
|
|
|
25 |
C |
p.
|
artikel
|
| 10 |
Geological object recognition in legacy maps through data augmentation and transfer learning techniques
|
Li, Wenjia
|
|
|
25 |
C |
p.
|
artikel
|
| 11 |
Irrigated rice-field mapping in Brazil using phenological stage information and optical and microwave remote sensing
|
Garcia, Andre Dalla Bernardina
|
|
|
25 |
C |
p.
|
artikel
|
| 12 |
Land use and land cover classification for change detection studies using convolutional neural network
|
Pushpalatha, V.
|
|
|
25 |
C |
p.
|
artikel
|
| 13 |
lasertram: A Python library for time resolved analysis of laser ablation inductively coupled plasma mass spectrometry data
|
Lubbers, Jordan
|
|
|
25 |
C |
p.
|
artikel
|
| 14 |
Predictive regressive models of recent marsh sediment thickness improve the quantification of coastal marsh sediment budgets
|
Smith, Christopher G.
|
|
|
25 |
C |
p.
|
artikel
|
| 15 |
Pymaginverse: A python package for global geomagnetic field modeling
|
Out, Frenk
|
|
|
25 |
C |
p.
|
artikel
|
| 16 |
Rapid mapping of landslides using satellite SAR imagery: A progressive learning approach
|
Prakash, Nikhil
|
|
|
25 |
C |
p.
|
artikel
|
| 17 |
Relationships between fault friction, slip time, and physical parameters explored by experiment-based friction model: A machine learning approach using recurrent neural networks (RNNs)
|
Uhmb, Tae-Hoon
|
|
|
25 |
C |
p.
|
artikel
|
| 18 |
SeisAug: A data augmentation python toolkit
|
Pragnath, D.
|
|
|
25 |
C |
p.
|
artikel
|
| 19 |
Semantic segmentation framework for atoll satellite imagery: An in-depth exploration using UNet variants and Segmentation Gym
|
Wang, Ray
|
|
|
25 |
C |
p.
|
artikel
|
| 20 |
Skillful prediction of Indian Ocean Dipole index using machine learning models
|
Ratnam, J.V.
|
|
|
25 |
C |
p.
|
artikel
|
| 21 |
Streamlining geoscience data analysis with an LLM-driven workflow
|
Zhang, Jiyin
|
|
|
25 |
C |
p.
|
artikel
|
| 22 |
X-ray Micro-CT based characterization of rock cuttings with deep learning
|
Olsen, Nils
|
|
|
25 |
C |
p.
|
artikel
|
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