Geologi lembar Jakarta dan Kepulauan Seribu, Jawa lembar 1209-4 & 1210-1 seka…

Edisi

-

ISBN/ISSN

-

Deskripsi Fisik

14 hlm. illus. 26 cm

Judul Seri

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No. Panggil

551 TUR g

Rock to riches: the story of Australia's national geological surveys

Edisi

-

ISBN/ISSN

1-86448-009-2

Deskripsi Fisik

xviii, 446 hlm. : illus.

Judul Seri

-

No. Panggil

R 551 Ric R

Teknik dan aplikasi geologi foto

Edisi

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ISBN/ISSN

979-426-277-3

Deskripsi Fisik

180 hlm. illus. 25 cm.

Judul Seri

-

No. Panggil

526.982 TUR t

Prosiding workshop geologi pegunungan selatan 2007

Edisi

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ISBN/ISSN

978-979-551-019-2

Deskripsi Fisik

iii, 233 hlm. : illus.

Judul Seri

-

No. Panggil

P 551.8 UDI p

Reconstruction of lithofacies using a supervised Self-Organizing Map: Applica…

Recently, machine learning (ML) has been considered a powerful technological element of different society areas. To transform the computer into a decision maker, several sophisticated methods and algorithms are constantly created and analyzed. In geophysics, both supervised and unsupervised ML methods have dramatically contributed to the development of seismic and well-log data interpretation. …

A study on geological structure prediction based on random forest method

The Xingmeng orogenic belt is located in the eastern section of the Central Asian orogenic belt, which is one of the key areas to study the formation and evolution of the Central Asian orogenic belt. At present, there is a huge controversy over the closure time of the Paleo-Asian Ocean in the Xingmeng orogenic belt. One of the reasons is that the genetic tectonic setting of the Carboniferous vo…

Geological object recognition in legacy maps through data augmentation and tr…

Maps are crucial tools in geosciences, providing detailed representations of the spatial distribution and relationships among geological features. Accurate recognition and classification of geological objects within these maps are essential for applications in resource exploration, environmental management, and geological hazard assessment. Along the years, many legacy geological maps have been…

Do more with less: Exploring semi-supervised learning for geological image cl…

Labelled datasets within geoscience can often be small, with data acquisition both costly and challenging, and their interpretation and downstream use in machine learning difficult due to data scarcity. Deep learning algorithms require large datasets to learn a robust relationship between the data and its label and avoid overfitting. To overcome the paucity of data, transfer learning has been e…

Classification of geological borehole descriptions using a domain adapted lar…

Geological borehole descriptions contain detailed textual information about the composition of the subsurface. However, their unstructured format presents significant challenges for extracting relevant features into a structured format. This paper introduces GEOBERTje: a domain adapted large language model trained on geological borehole descriptions from Flanders (Belgium) in the Dutch language…

An open-source, QGIS-based solution for digital geological mapping: GEOL-QMAPS

Digital geological mapping has experienced significant growth over the past three decades due to the advent of commercial geographical information systems, advances in global positioning systems, and the availability of portable hand-held devices, such as mobile personal computers (PCs), smartphones, and tablets. Numerous software packages have been developed to collect, combine, organise, visu…