Browsing by Author "Camalan, Mahmut"
Now showing items 1-4 of 4
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Assessment of chromite liberation spectrum on microscopic images by means of a supervised image classification
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Publisher and Date:(Elsevier Science Bv, 2017)Assessment of mineral liberation spectrum with all its aspects is essential for plant control and optimization. This paper aims to estimate 2D mineral map and its associated liberation spectrum of a particular chromite sample from optical micrographs by using Random Forest Classification a powerful machine-learning algorithm implemented on a user-friendly and an open-source software. This supervised classification method can be used to accurately generate 2D mineral map of this chromite sample. ...
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Development of a supervised classification method to construct 2D mineral maps on backscattered electron images
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Publisher and Date:(Tubitak, 2020)The Mineral Liberation Analyzer (MLA) can be used to obtain mineral maps from backscattered electron (BSE) images of particles. This paper proposes an alternative methodology that includes random forest classification, a prospective machine learning algorithm, to develop mineral maps from BSE images. The results show that the overall accuracy and kappa statistic of the proposed method are 97% and 0.94, respectively, proving that random forest classification is accurate. The accuracy indicators ...
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Sentinel-1 sar verileri kullanilanarak maden kaymalarini ve deformasyonlarini izleme [MONITORING of MINE LANDSLIDE and DEFORMATION USING SENTINEL-1 SAR DATA]
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Publisher and Date:(Baski, 2019)In this study, an original DInSAR method was used to monitor landslides and deformation in a coal mine area. The open-pit mine operation belonging to the Ciner Group in Silopi, Sirnak was selected fort he case study. Between 21 November 2017 and December 31, 2017, 2-month Sentinel-1 data were analyzed every 12 days and interferometric results were obtained. It has been shown that the DInSAR method can be used effectively in order to monitor the mineral movements by using satellite images. The ...
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Using Random Forest Tree Classification for Evaluating Vertical Cross-Sections in Epoxy Blocks to Get Unbiased Estimates for 3D Mineral Map
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Publisher and Date:(Gazi University, 2021)Areal mineral maps are constructed from the polished sections of particles that settle to the bottom of epoxy resin. However, heavy minerals can preferentially settle to the bottom, making the polished surface rich in heavy minerals. Therefore, polished sections will become biased estimates of the volumetric (3D) map. The study aims to test whether any vertical cross-section (any section along the settling direction of particles) can be an unbiased estimate of the 3D mineral map of a chromite ore ...
