首页|Data from Polytechnic University Milan Update Knowledge in Machine Learning (Sem antic Enrichment of BIM: The Role of Machine Learning-Based Image Recognition)
Data from Polytechnic University Milan Update Knowledge in Machine Learning (Sem antic Enrichment of BIM: The Role of Machine Learning-Based Image Recognition)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in artific ial intelligence. According to news reporting originating from Milano, Italy, by NewsRx correspondents, research stated, “Building Information Modelling (BIM) r evolutionizes the construction industry by digitally simulating real-world entit ies through a defined and shared semantic structure.” The news correspondents obtained a quote from the research from Polytechnic Univ ersity Milan: “However, graphical information included in BIM models often conta ins more detailed data compared to the corresponding semantic or computable data . This inconsistency creates an asymmetry, where valuable details present in the graphical renderings are absent from the semantic description of the model. Suc h an issue limits the accuracy and comprehensiveness of BIM models, constraining their full utilization for efficient decision-making and collaboration in the c onstruction process. To tackle this challenge, this paper presents a novel appro ach that utilizes Machine Learning (ML) to mediate the disparity between graphic al and semantic information.”
Polytechnic University MilanMilanoIt alyEuropeCyborgsEmerging TechnologiesMachine Learning
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