Natural language processing‐based deep transfer learning model across diverse tabular datasets for bond strength prediction of composite bars in concrete

Research article (Computer-Aided Civil and Infrastructure Engineering, 2024) · cited 29× · AI/ML
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Natural language processing‐based deep transfer learning model across diverse tabular datasets for bond strength prediction of composite bars in concrete

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Natural language processing‐based deep transfer learning model across diverse tabular datasets for bond strength prediction of composite bars in concrete is a scholarly article[1].

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  • Natural language processing‐based deep transfer learning model across diverse tabular datasets for bond strength prediction of composite bars in concrete's instance of is recorded as scholarly article[2].

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APA 4ort.xyz Knowledge Graph. (2026). Natural language processing‐based deep transfer learning model across diverse tabular datasets for bond strength prediction of composite bars in concrete. Retrieved May 24, 2026, from https://4ort.xyz/entity/natural-language-processingbased-deep-transfer-learning-model-across-diverse-tabular-datasets-for-bond-strength-predicti
MLA “Natural language processing‐based deep transfer learning model across diverse tabular datasets for bond strength prediction of composite bars in concrete.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/natural-language-processingbased-deep-transfer-learning-model-across-diverse-tabular-datasets-for-bond-strength-predicti.
BibTeX @misc{4ortxyz_natural-language-processingbased-deep-transfer-learning-model-across-diverse-tabular-datasets-for-bond-strength-predicti_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Natural language processing‐based deep transfer learning model across diverse tabular datasets for bond strength prediction of composite bars in concrete}}, year = {2026}, url = {https://4ort.xyz/entity/natural-language-processingbased-deep-transfer-learning-model-across-diverse-tabular-datasets-for-bond-strength-predicti}, note = {Accessed: 2026-05-24}}
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