May 7, 2024, 4:47 a.m. | Junjiang Zhen, Bojun Xie

cs.CV updates on arXiv.org arxiv.org

arXiv:2405.02785v1 Announce Type: new
Abstract: Deep learning has had a significant impact on the identification and classification of mineral resources, especially playing a key role in efficiently and accurately identifying different minerals, which is important for improving the efficiency and accuracy of mining. However, traditional ore sorting meth- ods often suffer from inefficiency and lack of accuracy, especially in complex mineral environments. To address these challenges, this study proposes a method called OreYOLO, which incorporates an attentional mechanism and a …

abstract accuracy arxiv attention classification cs.cv deep learning efficiency however identification impact improving key minerals mining network playing resources role sorting type

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