1 citations · 2 across the 4 of their papers we have counts for
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synth-dacl: Does Synthetic Defect Data Enhance Segmentation Accuracy and Robustness for Real-World Bridge Inspections?
Johannes Flotzinger, Fabian Deuser, Achref Jaziri +4
Adequate bridge inspection is increasingly challenging in many countries due to growing ailing stocks, compounded with a lack of staff and financial resources. Automating the key t…
dacl1k: Real-World Bridge Damage Dataset Putting Open-Source Data to the Test
Johannes Flotzinger, Philipp J. Rösch, Norbert Oswald +1
Recognising reinforced concrete defects (RCDs) is a crucial element for determining the structural integrity, traffic safety and durability of bridges. However, most of the existin…
dacl10k: Benchmark for Semantic Bridge Damage Segmentation
Johannes Flotzinger, Philipp J. Rösch, Thomas Braml
Reliably identifying reinforced concrete defects (RCDs)plays a crucial role in assessing the structural integrity, traffic safety, and long-term durability of concrete bridges, whi…
Building Inspection Toolkit: Unified Evaluation and Strong Baselines for Damage Recognition
Johannes Flotzinger, Philipp J. Rösch, Norbert Oswald +1
In recent years, several companies and researchers have started to tackle the problem of damage recognition within the scope of automated inspection of built structures. While comp…