A review of artificial intelligence technologies in mineral identification : classification and visualization

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dc.contributor.author Long, Teng
dc.contributor.author Zhou, Zhangbing
dc.contributor.author Hancke, Gerhard P.
dc.contributor.author Bai, Yang
dc.contributor.author Gao, Qi
dc.date.accessioned 2022-12-15T10:47:19Z
dc.date.available 2022-12-15T10:47:19Z
dc.date.issued 2022-08-29
dc.description.abstract Artificial intelligence is a branch of computer science that attempts to understand the essence of intelligence and produce a new intelligent machine capable of responding in a manner similar to human intelligence. Research in this area includes robotics, language recognition, image identification, natural language processing, and expert systems. In recent years, the availability of large datasets, the development of effective algorithms, and access to powerful computers have led to unprecedented success in artificial intelligence. This powerful tool has been used in numerous scientific and engineering fields including mineral identification. This paper summarizes the methods and techniques of artificial intelligence applied to intelligent mineral identification based on research, classifying the methods and techniques as artificial neural networks, machine learning, and deep learning. On this basis, visualization analysis is conducted for mineral identification of artificial intelligence from field development paths, research hot spots, and keywords detection, respectively. In the end, based on trend analysis and keyword analysis, we propose possible future research directions for intelligent mineral identification. en_US
dc.description.department Electrical, Electronic and Computer Engineering en_US
dc.description.sponsorship The National Natural Science Foundation of China. en_US
dc.description.uri https://www.mdpi.com/journal/jsan en_US
dc.identifier.citation Long, T.; Zhou, Z.; Hancke, G.; Bai, Y.; Gao, Q. A Review of Artificial Intelligence Technologies in Mineral Identification: Classification and Visualization. Journal of Sensor and Actuator Networks 2022, 11, 50. https://doi.org/10.3390/jsan11030050. en_US
dc.identifier.issn 2224-2708 (online)
dc.identifier.other 10.3390/jsan11030050
dc.identifier.uri https://repository.up.ac.za/handle/2263/88833
dc.language.iso en en_US
dc.publisher MDPI en_US
dc.rights © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). en_US
dc.subject Mineral identification en_US
dc.subject Deep learning en_US
dc.subject Visualization analysis en_US
dc.subject Artificial intelligence (AI) en_US
dc.title A review of artificial intelligence technologies in mineral identification : classification and visualization en_US
dc.type Article en_US


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