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Article summary:

1. This article presents a new method for automatically extracting rock mass structure information from multiview images.

2. The proposed algorithm integrates a full convolutional network (FCN) and multimodal semantic features to map the relationship between pixels and their surrounding grid cells.

3. Experiments using columnar basalt image data demonstrate the feasibility and accuracy of the proposed algorithm.

Article analysis:

The article is generally reliable, as it provides a detailed description of the proposed method for automatically extracting rock mass structure information from multiview images, as well as experiments conducted to demonstrate its feasibility and accuracy. The authors provide evidence for their claims by citing relevant research in the field, which adds credibility to their work. Furthermore, they discuss potential limitations of their approach, such as its reliance on accurate camera calibration and the difficulty of obtaining accurate results with traditional image pixel segmentation methods.

However, there are some points that could be improved upon in terms of trustworthiness and reliability. For example, while the authors discuss potential limitations of their approach, they do not explore possible counterarguments or alternative solutions to these issues. Additionally, while they cite relevant research in the field, they do not provide an exhaustive list of all related studies that could have been included in order to provide a more comprehensive overview of existing approaches in this area. Finally, there is no discussion of potential risks associated with using this method or any ethical considerations that should be taken into account when applying it in practice.