Scanline intersection similarity: A similarity metric for joint trace maps

Kim, Jineon; Lee, Yong-ki; Choi, Choongik; Fereshtenejad, Sayedalireza; Song, Jae-Joon

doi:10.1016/j.cageo.2023.105358

Cited by 2 publications

(1 citation statement)

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“…Lee et al [25] obtained a Jaccard index of 62% for a similar purpose. With the development of geometry-based evaluation criteria, the model scores for rock discontinuities can gain more reliability [70]. When visually inspecting the model predictions, it was observed that discontinuities were detected as partial lines.…”

Section: Discussionmentioning

confidence: 99%

A Novel Rock Mass Discontinuity Detection Approach with CNNs and Multi-View Image Augmentation

Yalcin,

Can,

Gokceoglu

et al. 2024

IJGI

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Discontinuity is a key element used by geoscientists and civil engineers to characterize rock masses. The traditional approach to detecting and measuring rock discontinuity relies on fieldwork, which poses dangers to human life. Photogrammetric pattern recognition and 3D measurement techniques offer new possibilities without direct contact with rock masses. This study proposes a new approach to detect discontinuities using close-range photogrammetric techniques and convolutional neural networks (CNNs) trained on a small amount of data. Investigations were conducted on basalts in Bala, Ankara, Türkiye. A total of 34 multi-view images were collected with a remotely piloted aircraft system (RPAS), and discontinuity lines were manually delineated on a point cloud generated from these images. The lines were back-projected onto the raw images to increase the amount of data, a process we call multi-view (3D) augmentation. We further evaluated radiometric and geometric augmentation methods, the contribution of multi-view augmentation to the proposed model, and the transfer learning performance of six different CNN architectures. The highest performance was achieved with U-Net + SE-ResNeXt-50 with an F1-score of 90.6%. The CNN model trained from scratch with local features also yielded a similar F1-score (91.7%), which is the highest performance reported in the literature.

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Section: Discussionmentioning

confidence: 99%