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References from On-site lithology identification for tunnel face via self-supervised learning on TBM muck images. Local targets link to admitted publications; unresolved targets remain external evidence.
Automated lithology classification from drill core images using convolutional neural networks
10.1016/j.petrol.2020.107933 · 2021 · External reference
Diameter-independent indices for TBM rock-mass classification
10.1016/j.tust.2026.107584 · 2026 · External reference
A simple framework for contrastive learning of visual representations
2020 · External reference
Automated extraction and evaluation of fracture trace maps from rock tunnel face images via deep learning
10.1016/j.ijrmms.2021.104745 · 2021 · External reference
Classification prediction of surrounding rock based on TBM muck images
2024 · External reference
Comparison and analysis of denoising method in TBM key tunnelling data
2025 · External reference
Recognizing multiple types of rocks quickly and accurately based on lightweight CNNs model
10.1109/access.2020.2982017 · 2020 · External reference
Influence of rock brittleness on TBM penetration rate in Singapore granite
10.1016/j.tust.2006.07.004 · 2007 · External reference
Development of a real-time muck analysis system for assistant intelligence TBM tunnelling
10.1016/j.tust.2020.103655 · 2021 · External reference
A deep neural network model for parameter identification in deep drawing metal forming process
10.1016/j.jmapro.2024.11.067 · 2025 · External reference
Deep residual learning for image recognition
2016 · External reference
Deep learning-based instance segmentation of cracks from shield tunnel lining images
10.1080/15732479.2020.1838559 · 2022 · External reference
TBM rock fragmentation classification using an adaptive spot denoising and contour-texture decomposition attention-based method
10.1016/j.tust.2025.106498 · 2025 · External reference
A novel multi-scale hybrid connected neural network for anti-noise rock fragmentation classification of tunnel boring machine
10.1016/j.tust.2025.106555 · 2025 · External reference
A real-time rock mass class identification model of the tunnel face based on TBM tunneling and the corresponding muck characteristic parameters
10.1016/j.ijrmms.2025.106057 · 2025 · External reference
A deep neural network approach to predict dimensional accuracy of thin-walled tubes in backward flow forming plasticity process
10.1016/j.jmapro.2025.02.044 · 2025 · External reference
Feedback on a shared big dataset for intelligent TBM Part II: Application and forward look
10.1016/j.undsp.2023.01.002 · 2023 · External reference
Development and experimental verification of a new model for predicting laser-induced rock cutting slit depth
10.1016/j.ijrmms.2024.105722 · 2024 · External reference
Lithology dataset of remote sensing image in Changbaishan volcano based on semantic segmentation
10.18654/1000-0569/2025.04.17 · 2025 · External reference
Towards automated lithology classification in NATM tunnel: A data-driven solution for multi-dimensional imbalanced data
10.1007/s00603-024-04287-6 · 2025 · External reference
Hard-rock tunnel lithology prediction with TBM construction big data using a global-attention-mechanism-based LSTM network
10.1016/j.autcon.2021.103647 · 2021 · External reference
Characterization of particle size distribution of rock chips and evaluation of rock breaking efficiency of TBM based on multifractal theory: A case study
10.1016/j.tust.2025.106418 · 2025 · External reference
Simultaneous imposition of initial and boundary conditions via decoupled physics-informed neural networks for solving initial-boundary value problems
10.1007/s10483-025-3240-7 · 2025 · External reference
A data-driven uncertainty quantification framework in probabilistic bio-inspired porous materials (Material-UQ): An investigation for RotTMPS plates
10.1016/j.cma.2024.117603 · 2025 · External reference
Deep neural network and evolved optimization algorithm for damage assessment in a truss bridge
10.3390/math12152300 · 2024 · External reference
Multi-domain masked reconstruction self-supervised learning for lithology identification using well-logging data
10.1016/j.knosys.2025.113843 · 2025 · External reference
Developing Estimation Equations for the Cerchar Abrasivity Index of Rocks Applicable to TBM Tunnels
10.1007/s00603-024-04015-0 · 2024 · External reference
Refined lithology identification: Methodology, challenges and prospects
10.1016/j.geoen.2023.212382 · 2023 · External reference
Fast reservoir characterization with AI-based lithology prediction using drill cuttings images and noisy labels
10.3390/jimaging9070126 · 2023 · External reference
Fusion of convolution neural network and visual transformer for lithology identification using tunnel face images
10.1061/jccee5.cpeng-5997 · 2025 · External reference
Influence of neural network structure on rock intelligent classification based on structural and tectonic features of rocks
10.1007/s00603-022-02907-7 · 2022 · External reference
Deep learning-based prediction of steady surface settlement due to shield tunnelling
10.1016/j.autcon.2023.105006 · 2023 · External reference
Estimation of load for tunnel lining in elastic soil using physics‐informed neural network
10.1111/mice.13208 · 2024 · External reference
Influences of bit button wear on performance of rotary-percussive drilling: MBD-DEM coupling simulation and verification
10.1016/j.jrmge.2024.08.004 · 2025 · External reference
Real-time perception of rock–machine interaction information in TBM tunnelling using muck image analysis
10.1016/j.tust.2023.105096 · 2023 · External reference
Water saturation effects on rock abrasivity and TBM tunneling efficiency
2024 · External reference
Classification of rock fragments produced by tunnel boring machine using convolutional neural networks
10.1016/j.autcon.2021.103612 · 2021 · External reference
Feature fusion method for rock mass classification prediction and interpretable analysis based on TBM operating and cutter wear data
10.1016/j.tust.2024.106351 · 2025 · External reference
A multi-channel decoupled deep neural network for tunnel boring machine torque and thrust prediction
10.1016/j.tust.2022.104949 · 2023 · External reference
Hard-rock tunnel lithology identification using multi-scale dilated convolutional attention network based on tunnel face images
10.1007/s11709-023-0002-1 · 2023 · External reference
Automatic segmentation of TBM muck images via a deep-learning approach to estimate the size and shape of rock chips
10.1016/j.autcon.2021.103685 · 2021 · External reference
TBM cutter wear under high-strength surrounding rock conditions: A case study from the second phase of the Northern Xinjiang water supply project
10.1007/s00603-021-02545-5 · 2021 · External reference
A comparative analysis of hybrid RF models for efficient lithology prediction in hard rock tunneling using TBM working parameters
10.1007/s11600-024-01320-8 · 2024 · External reference
Optimized decision-making for tunnel boring machine control parameters
10.1007/s00603-025-04451-6 · 2025 · External reference
