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DeepCrackAT: An effective crack segmentation framework based on learning multi-scale crack features

Research article (Engineering Applications of Artificial Intelligence, 2023) · cited 61× · AI/ML
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DeepCrackAT: An effective crack segmentation framework based on learning multi-scale crack features

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DeepCrackAT: An effective crack segmentation framework based on learning multi-scale crack features is a scholarly article[1].

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  • DeepCrackAT: An effective crack segmentation framework based on learning multi-scale crack features's instance of is recorded as scholarly article[2].

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  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). DeepCrackAT: An effective crack segmentation framework based on learning multi-scale crack features. Retrieved May 24, 2026, from https://4ort.xyz/entity/deepcrackat-an-effective-crack-segmentation-framework-based-on-learning-multi-scale-crack-features
MLA “DeepCrackAT: An effective crack segmentation framework based on learning multi-scale crack features.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/deepcrackat-an-effective-crack-segmentation-framework-based-on-learning-multi-scale-crack-features.
BibTeX @misc{4ortxyz_deepcrackat-an-effective-crack-segmentation-framework-based-on-learning-multi-scale-crack-features_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{DeepCrackAT: An effective crack segmentation framework based on learning multi-scale crack features}}, year = {2026}, url = {https://4ort.xyz/entity/deepcrackat-an-effective-crack-segmentation-framework-based-on-learning-multi-scale-crack-features}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): DeepCrackAT: An effective crack segmentation framework based on learning multi-scale crack features — https://4ort.xyz/entity/deepcrackat-an-effective-crack-segmentation-framework-based-on-learning-multi-scale-crack-features (retrieved 2026-05-24)

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