The International Journal of Applied Radiation and Isotopes
Dual energy gamma-ray transmission techniques applied to on-line analysis in the coal and mineral industries
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2023, Computers and GeosciencesOre image classification based on small deep learning model: Evaluation and optimization of model depth, model structure and data size
2021, Minerals EngineeringCitation Excerpt :At this stage, intelligent dry separation equipment has been applied in underground gangue discharge or ore pre-separation, significantly reducing the energy consumption in the crushing process and reagent consumption in the flotation process, further improving production efficiency and reducing pollution treatment cost. In the current market, the mainstream intelligent ore sorting equipment used into production are based on ray-based sensors, such as γ-ray (Watt and Steffner, 1985), Raman spectrum analysis (Ishikawa and Gulick, 2013), XRT (Robben et al., 2020), XRF (Li et al., 2019). Radiation-based sensors have high classification accuracy and are mostly used to identify and separate large ore blocks.
Performance evaluation of a deep learning based wet coal image classification
2021, Minerals EngineeringCitation Excerpt :At present, sensor-based ore sorting technology is mainly divided into two types: ray sensor-based and machine vision-based. Specifically, the ray sensor-based ore sorting equipment mainly takes γ-ray (Watt and Steffner, 1985), Raman spectrum (Das and Hendry, 2011; Frost, 2003; Ishikawa and Gulick, 2013), X-ray diffraction (XRD) (Robben et al., 2020), and X-ray fluorescence spectrometry (XRF) as the technical foundation (Karna et al., 2016; Knapp et al., 2014). The machine vision-based ore sorting equipment mainly consists of the visible light sensor and the near-infrared sensor (Grant et al., 2018).