Abstract
Yang Wen, Xiangui Wang, Zhaibang Ke, Wenkang Zhang
Abstract
Authors
Institutions
Provenance
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No local citing links have been materialized yet.
10.3390/coatings15070836
10.3390/coatings15070836
10.3390/ma18071611
10.3390/ma18071611
Computer vision framework for crack detection of civil infrastructure—A review
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UMDA: Lightweight and efficient crack segmentation model
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VTECSeg: Edge-aware hybrid CNN-vision transformer network with zero-shot vision-language-guided region proposals for crack segmentation
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10.3390/buildings13123095
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openalex
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datacite
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10.3390/buildings13123114
10.3390/buildings13123114
10.3390/buildings14082360
10.3390/buildings14082360
Vision-guided robot for automated pixel-level pavement crack sealing
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Complete and near-optimal robotic crack coverage and filling in civil infrastructure
10.1109/tro.2024.3392077 · 2024
Recent advancements of robotics in construction
10.1016/j.autcon.2022.104591 · 2022
Robotics in the construction sector: Trends, advances, and challenges
10.1007/s10846-024-02104-4 · 2024
Coverage for robotics–A survey of recent results
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10.3390/s21237898
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A hybrid guided local search for the vehicle-routing problem with intermediate replenishment facilities
10.1287/ijoc.1070.0230 · 2008
The electric vehicle routing problem and its variations: A literature review
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Multi-day routes in a multi-depot vehicle routing problem with intermediate replenishment facilities and time windows
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10.1287/trsc.1050.0135 · 2006
A review and ranking of operators in adaptive large neighborhood search for vehicle routing problems
10.1016/j.ejor.2024.05.033 · 2025
A modified orthonormal polynomial series expansion tailored to thin beams undergoing slamming loads
10.1016/j.oceaneng.2019.04.060 · 2019
Route first–cluster second methods for vehicle routing
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Integer programming formulation of traveling salesman problems
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Integer programming formulation of traveling salesman problems
10.1145/321043.321046 · doi-reference
Route first–cluster second methods for vehicle routing
10.1016/0305-0483(83)90033-6 · doi-reference
A modified orthonormal polynomial series expansion tailored to thin beams undergoing slamming loads
10.1016/j.oceaneng.2019.04.060 · doi-reference
A review and ranking of operators in adaptive large neighborhood search for vehicle routing problems
10.1016/j.ejor.2024.05.033 · doi-reference
An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows
10.1287/trsc.1050.0135 · doi-reference
Multi-day routes in a multi-depot vehicle routing problem with intermediate replenishment facilities and time windows
10.1016/j.cor.2025.107084 · doi-reference
The electric vehicle routing problem and its variations: A literature review
10.1016/j.cie.2021.107650 · doi-reference
A hybrid guided local search for the vehicle-routing problem with intermediate replenishment facilities
10.1287/ijoc.1070.0230 · doi-reference
Algorithms for the vehicle routing and scheduling problems with time window constraints
10.1287/opre.35.2.254 · doi-reference
The truck dispatching problem
10.1287/mnsc.6.1.80 · doi-reference
The orienteering problem: A survey
10.1016/j.ejor.2010.03.045 · doi-reference
10.3390/s21237898
10.3390/s21237898 · doi-reference
Coverage for robotics–A survey of recent results
10.1023/a:1016639210559 · doi-reference
Robotics in the construction sector: Trends, advances, and challenges
10.1007/s10846-024-02104-4 · doi-reference
Recent advancements of robotics in construction
10.1016/j.autcon.2022.104591 · doi-reference
Complete and near-optimal robotic crack coverage and filling in civil infrastructure
10.1109/tro.2024.3392077 · doi-reference
Vision-guided robot for automated pixel-level pavement crack sealing
10.1016/j.autcon.2024.105783 · doi-reference
10.3390/buildings14082360
10.3390/buildings14082360 · doi-reference
10.3390/buildings13123114
10.3390/buildings13123114 · doi-reference
10.3390/buildings13123095
10.3390/buildings13123095 · doi-reference
10.3390/buildings13071814
10.3390/buildings13071814 · doi-reference
VTECSeg: Edge-aware hybrid CNN-vision transformer network with zero-shot vision-language-guided region proposals for crack segmentation
10.1016/j.autcon.2026.106998 · doi-reference
UMDA: Lightweight and efficient crack segmentation model
10.1061/jccee5.cpeng-6951 · doi-reference
Pavement crack detection based on transformer network
10.1016/j.autcon.2022.104646 · doi-reference
CrackW-Net: A novel pavement crack image segmentation convolutional neural network
10.1109/tits.2021.3095507 · doi-reference
Automated pavement crack segmentation using U-Net-based convolutional neural network
10.1109/access.2020.3003638 · doi-reference
Computer vision framework for crack detection of civil infrastructure—A review
10.1016/j.engappai.2022.105478 · doi-reference
10.3390/ma18071611
10.3390/ma18071611 · doi-reference
10.3390/coatings15070836
10.3390/coatings15070836 · doi-reference