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BILT ANZ 2022, Gold Coast
24 - 26 November, 2022
BILT ANZ 2022, Gold Coast

Session 1.2

Thursday, 24 November, 2022 | 11:30 AM

Automated Revit Documentation Via Machine Learning

Brenden Picton, GHD
Not Applicable
BILT
Coding and Customisation
Non Vendor Specific
Presentation/Lecture
Advanced
BIM Leaders/Managers, Data Scientists/Analysts/Wranglers

Synopsis:

This class will look at an internal project GHD recently undertook to establish the viability of using machine learning for the automatic placement of tags using several machine learning algorithms. We will look into 2 different algorithms, convolutional neural network approach using tagged images, and a tabular approach for the semantic data of the tags. We’ll step through the problem state, how we captured the data and then the outcomes/accuracy of the algorithms that we tested.

Learning Objectives:

1. Learn different machine learning approaches
2. Strategies to capture Revit data for training ML algorithms
3. Comparison and analysis of different algorithms

Body:

This class will look at an internal project GHD recently undertook to establish the viability of using machine learning for the automatic placement of tags using several machine learning algorithms. We will look into 2 different algorithms, convolutional neural network approach using tagged images, and a tabular approach for the semantic data of the tags. We’ll step through the problem state, how we captured the data and then the outcomes/accuracy of the algorithms that we tested.

Speakers:

Speaker

Brenden Picton

GHD
Automation and Computational BIM Leader

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Registration Conditions

DIGITAL BUILT WEEK AMERICAS 2023 (“Conference”) 15 – 17 June 2023 will be held at the Kay Bailey Hutchison Convention Center, Dallas, Texas.The Organizer (“Organizers”) of the Conference is the Digital Built Environment Institute USA, INC (DBEI).

3943 Irvine Blvd. - Suite 13 Irvine, CA 92602 USA

Phone: +1 213 814 2888

All inquiries relating to these matters should be directed to DBEI’s Marketing Team at info@dbei.org.

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