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Deep autoencoder architecture for bridge damage assessment using responses from several vehicles

Research article (Engineering Structures, 2021) · cited 94× · AI/ML
academia openalex:W3196518276
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Deep autoencoder architecture for bridge damage assessment using responses from several vehicles

Summary

Deep autoencoder architecture for bridge damage assessment using responses from several vehicles is a scholarly article[1].

Key Facts

  • Deep autoencoder architecture for bridge damage assessment using responses from several vehicles'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). Deep autoencoder architecture for bridge damage assessment using responses from several vehicles. Retrieved May 24, 2026, from https://4ort.xyz/entity/deep-autoencoder-architecture-for-bridge-damage-assessment-using-responses-from-several-vehicles
MLA “Deep autoencoder architecture for bridge damage assessment using responses from several vehicles.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/deep-autoencoder-architecture-for-bridge-damage-assessment-using-responses-from-several-vehicles.
BibTeX @misc{4ortxyz_deep-autoencoder-architecture-for-bridge-damage-assessment-using-responses-from-several-vehicles_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Deep autoencoder architecture for bridge damage assessment using responses from several vehicles}}, year = {2026}, url = {https://4ort.xyz/entity/deep-autoencoder-architecture-for-bridge-damage-assessment-using-responses-from-several-vehicles}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Deep autoencoder architecture for bridge damage assessment using responses from several vehicles — https://4ort.xyz/entity/deep-autoencoder-architecture-for-bridge-damage-assessment-using-responses-from-several-vehicles (retrieved 2026-05-24)

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