Ditapis dengan
Resolution enhancement and segmentation of polar bubbly ice micro CT scans vi…
Accurate segmentation of 3D micro CT scans is a key step in the process of analysis of the microstructure of porous materials. In polar ice core studies, the environmental effects on the firn column could be detected if the microstructure is digitized accurately. The most challenging task is to obtain the microstructure parameters of the bubbly ice section. To identify the minimum, necessary re…
- Edisi
- Vol.23, September 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 13 hlm PDF, 3.950 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Advancing geological image segmentation: Deep learning approaches for rock ty…
This study aims to tackle the obstacles linked with geological image segmentation by employing sophisticated deep learning techniques. Geological formations, characterized by diverse forms, sizes, textures, and colors, present a complex landscape for traditional image processing techniques. Drawing inspiration from recent advancements in image segmentation, particularly in medical imaging and o…
- Edisi
- Vol.23, September 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 16 hlm PDF, 17.044 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
A new approach to dust source mapping using visual interpretation and object-…
The emission of dust particles, mainly from arid and semi-arid lands, as a result of climate change and human activities, is known to be a global issue. Identifying dust emission sources is the first key step in dealing with the hazardous consequences of this rising phenomenon. This study is an attempt to address one of the major challenges in mapping dust emission sources. Accordingly, an inno…
- Edisi
- Vol.23, September 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 9 hlm PDF, 13.165 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Machine learning – An approach for consistent rock glacier mapping and inve…
Rock glaciers (RG) are landforms that occur in high latitudes or elevations and — in their active state — consist of a mixture of rock debris and ice. Despite serving as a form of groundwater storage, they are an indicator for the occurrence of (former) permafrost and therefore carry significance in the research for the ongoing climate change. For these reasons, the past years have shown ri…
- Edisi
- Vol.16, December 2022
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 12 hlm PDF, 13.829 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Evaluating deep-learning models for debris-covered glacier mapping
In recent decades, mountain glaciers have experienced the impact of climate change in the form of accelerated glacier retreat and other glacier-related hazards such as mass wasting and glacier lake outburst floods. Since there are wide-ranging societal consequences of glacier retreat and hazards, monitoring these glaciers as accurately and repeatedly as possible is important. However, the accur…
- Edisi
- Vol.12, December 2021
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 17 hlm PDF, 31.040 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Towards global scale segmentation with OpenStreetMap and remote sensing
Land Use Land Cover (LULC) segmentation is a famous application of remote sensing in an urban environment. Up-to-date and complete data are of major importance in this field. Although with some success, pixel-based segmentation remains challenging because of class variability. Due to the increasing popularity of crowd-sourcing projects, like OpenStreetMap, the need for user-generated content ha…
- Edisi
- Vol.8, April 2023
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 12 hlm PDF, 13.029 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Deep learning approach for Sentinel-1 surface water mapping leveraging
Satellite remote sensing plays an important role in mapping the location and extent of surface water. A variety of approaches are available for mapping surface water, but deep learning approaches are not commonplace as they are ‘data hungry’ and require large amounts of computational resources. However, with the availability of various satellite sensors and rapid development in cloud comput…
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 13 hlm PDF, 4.033 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
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