A Review of AI for Efficient Mineral Identification
DOI:
https://doi.org/10.5281/zenodo.13631172Anahtar Kelimeler:
Artificial intelligence (AI), , Machine learning (ML), , Deep learning (DL), , Automated mineralogy,, Intelligent mineral identification,, Mineral classificationÖzet
The ability to identify minerals efficiently and accurately is crucial for various scientific and engineering fields. This paper explores the burgeoning role of artificial intelligence (AI) in revolutionizing mineral identification. We delve into the recent advancements in AI, particularly artificial neural networks, machine learning, and deep learning, and their application in this domain. Through visualization analysis, we trace the developmental trajectory of AI-powered mineral identification, pinpointing research hotspots and emerging keywords. Leveraging trend and keyword analyses, we propose promising avenues for future research, paving the way for further advancements in this exciting field. This abstract avoids directly mentioning computer science or replicating the original structure. It focuses on the specific application of AI in mineral identification, highlighting the advancements and future directions.
Keywords: Artificial intelligence (AI), Machine learning (ML), Deep learning (DL), Automated mineralogy, Intelligent mineral identification, Mineral classification
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