Two research papers, submitted to arXiv, explore methods for extracting procedural knowledge from industrial troubleshooting guides. The first paper evaluates Vision Language Models (VLMs) for this task, comparing standard instruction-guided prompting with an augmented approach that highlights layout patterns. The second paper introduces FlowExtract, a pipeline that uses YOLOv8 and EasyOCR for element detection and a novel edge detection method to reconstruct directed graphs from flowcharts, outperforming VLMs in edge extraction. AI
IMPACT Develops new methods for making industrial procedural knowledge machine-readable, potentially improving operator support systems.
RANK_REASON Two academic papers published on arXiv detailing methods for knowledge extraction from industrial diagrams.
- alphaXiv
- arXiv
- CatalyzeX
- DagsHub
- EasyOCR
- FlowExtract
- Guillermo Gil De Avalle
- Hugging Face
- ISO 5807
- Vision Language Models
- YOLOv8
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