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Damage identification based on convolutional neural network and recurrence graph for beam bridge

Research article (Structural Health Monitoring, 2020) · cited 57× · AI/ML
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Damage identification based on convolutional neural network and recurrence graph for beam bridge

Summary

Damage identification based on convolutional neural network and recurrence graph for beam bridge is a scholarly article[1].

Key Facts

  • Damage identification based on convolutional neural network and recurrence graph for beam bridge's instance of is recorded as scholarly article[2].

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Damage identification based on convolutional neural network and recurrence graph for beam bridge. Retrieved May 24, 2026, from https://4ort.xyz/entity/damage-identification-based-on-convolutional-neural-network-and-recurrence-graph-for-beam-bridge
MLA “Damage identification based on convolutional neural network and recurrence graph for beam bridge.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/damage-identification-based-on-convolutional-neural-network-and-recurrence-graph-for-beam-bridge.
BibTeX @misc{4ortxyz_damage-identification-based-on-convolutional-neural-network-and-recurrence-graph-for-beam-bridge_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Damage identification based on convolutional neural network and recurrence graph for beam bridge}}, year = {2026}, url = {https://4ort.xyz/entity/damage-identification-based-on-convolutional-neural-network-and-recurrence-graph-for-beam-bridge}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Damage identification based on convolutional neural network and recurrence graph for beam bridge — https://4ort.xyz/entity/damage-identification-based-on-convolutional-neural-network-and-recurrence-graph-for-beam-bridge (retrieved 2026-05-24)

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