University of Twente Student Theses

Login
As of Friday, 8 August 2025, the current Student Theses repository is no longer available for thesis uploads. A new Student Theses repository will be available starting Friday, 15 August 2025.

Multi-modal Document Classification in Architecture, Engineering, and Construction Asset Management Applications

Rademaker, F.M. (2025) Multi-modal Document Classification in Architecture, Engineering, and Construction Asset Management Applications.

[img] PDF
6MB
Abstract:The digitalisation of asset management within the architecture, engineering and construction (AEC) sector is in need of effective methods for the automatic classification of documents. This study focuses on the development and the evaluation of multimodal document classification models, utilizing visual, textual, and layout-related information. By using the CRISP-ML(Q) methodology as well as Neural Architecture Search, we examine various state-of-the-art machine learning models, and combine them through an iterative development process. The performances of these models are evaluated on two different AEC-document datasets. The results demonstrate that each of the modalities is useful in classifying the documents, as well as the integration of the different information types. This study contributes by applying AI techniques, specifically document classification in the AEC sector, setting the initial step to automating information extraction and processing for Intelligent Asset Management, and lastly, by combining and comparing multimodal state-of-the-art classification models on real life datasets.
Item Type:Essay (Master)
Clients:
Movares, Utrecht, Nederland
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science, 56 civil engineering
Programme:Business Information Technology MSc (60025)
Link to this item:https://purl.utwente.nl/essays/106897
Export this item as:BibTeX
EndNote
HTML Citation
Reference Manager

 

Repository Staff Only: item control page