Ditapis dengan
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
Comparative performance analysis of simple U-Net, residual attention U-Net, a…
Inland water bodies play a vital role at all scales in the terrestrial water balance and Earth’s climate variability. Thus, an inventory of inland waters is crucially important for hydrologic and ecological studies and management. Therefore, the main aim of this study was to develop a deep learning-based method for inventorying and mapping inland water bodies using the RGB band of high-resolu…
- Edisi
- Vol.21, March 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 11 hlm PDF, 3.036 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Where are the outcrops? Automatic delineation of bedrock from sediments using…
The delineating of bedrock from sediment is one of the most important phases in the fundamental process of regional bedrock identification and mapping, and it is usually manually performed using high-resolution optical remote-sensing images or Light Detection and Ranging (LiDAR) data. This task, although straightforward, is time consuming and requires extensive and specialized labor. We contrib…
- Edisi
- Vol.18 June 2023
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 10 hlm PDF, 10.364 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Rapid estimation of minimum depth-to-bedrock from lidar leveraging deep-learn…
Previously glaciated landscapes often share similar surficial characteristics, including large areas of exposed bedrock, blankets of till deposits, and alluvium-floored valleys. These materials play significant roles in geologic and hydrologic resources, geohazards, and landscape evolution; however, the vast extents of many previously glaciated landscapes have rendered comprehensive, detailed f…
- Edisi
- Vol.18 June 2023
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 11 hlm PDF, 9.277 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Rock type classification based on petrophysical, geochemical, and core imagin…
Rock type classification is one of the most crucial steps of geological and geotechnical core logging. In conventional core logging, rock type classification is subjective and time-consuming. This study aims to automate rock type classification using Machine Learning (ML). About 35 m of core samples from five different rock types obtained from an open pit mine were logged using a Multi-Sensor C…
- Edisi
- Vol.16, December 2022
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 13 hlm PDF, 10.764 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Automated detection of microfossil fish teeth from slide images using combine…
Microfossil fish teeth, known as ichthyoliths, provide a key constraint on the depositional age and environment of deep-sea sediments, especially pelagic clays where siliceous and calcareous microfossils are rarely observed. However, traditional methods for the observation of ichthyoliths require considerable time and manual labor, which can hinder their wider application. In this study, we con…
- Edisi
- Vol.16, December 2022
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 8 hlm PDF, 4.635 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Automatic classification of plutonic rocks with deep learning
Igneous rocks form when molten magma is cooled and solidified, either within the Earth’s crust (plutonic rocks), or from lava extruded onto the Earth’s surface in the atmosphere or underwater (volcanic rocks). The classification of igneous rocks can be done using data from different instrumental techniques. However, these approaches tend to be expensive and time-consuming. In this research …
- Edisi
- Vol.10, June 2021
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 8 h lm PDF, 2.214 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Using three dimensional convolutional neural networks for denoising echosound…
It is estimated that over 80% of the world’s oceans are unexplored and unmapped limiting our understanding of ocean systems. Due to data collection rates of modern survey technologies such as swathe multibeam echosounders (MBES) and initiatives such as Seabed 2030, there is ever-increasing increasing volume of seafloor data collected. These large data volumes present significant challenges ar…
- Edisi
- Vol.5, March 2020
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 10 hlm PDF, 2.691 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Transfer learning and single-polarized SAR image preprocessing for oil spill …
This study addresses the challenge of oil spill detection using Synthetic Aperture Radar (SAR) satellite imagery, employing deep learning techniques to improve accuracy and efficiency. We investigated the effectiveness of various neural network architectures and encoders for this task, focusing on scenarios with limited training data. The research problem centered on enhancing feature extractio…
- Edisi
- Vol.15, January 2025
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 8 hlm PDF, 1.441 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Comparing Deep Learning models for mapping rice cultivation area in Bhutan us…
Crop type and crop extent are critical information that helps policymakers make informed decisions on food security. As the economic growth of Bhutan has increased at an annual rate of 7.5% over the last three decades, there is a need to provide geospatial products that can be leveraged by local experts to support decision-making in the context of economic and population growth effects and impa…
- Edisi
- Vol.15, January 2025
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 17 hlm PDF, 9.124 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Batas Wilayah 
Ekologi 
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Geografi 
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Kartografi 
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