Post, August 7, 2026 • (University of North Dakota) SDNET2021 is a uniquely validated annotated dataset for evaluating the condition of concrete bridge decks and benchmarking advanced deep learning models for defects (delamination, cracks, rebar corrosion) detection and bridge deck evaluation. SDNET2021 contains 1,936 annotated IE signals, over 663,102 annotated GPR signals and five (5)...
University of North Dakota
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SDNET2021: Annotated NDE Dataset for Structural Defects
Post, November 13, 2025 • (University of North Dakota) SDNET2021 is a uniquely validated annotated dataset for evaluating the condition of concrete bridge decks and benchmarking advanced deep learning models for defects (delamination, cracks, rebar corrosion) detection and bridge deck evaluation. Common structural defects, such as cracks, delamination, spalling, rebar corrosion, etc. are commonly detected...