Towards Digitisation of Technical Drawings in Architecture: Evaluation of CNN Classification on the Perdaw Dataset

Alexandru Filip, Stella Graßhof

Publikation: Konference artikel i Proceeding eller bog/rapport kapitelKonferencebidrag i proceedingsForskningpeer review

Abstract

In a highly digitalised world, this paper aims at closing the gap towards automatic digitisation from 2D architectural drawings. We present the new image dataset Plan, and Elevation Representations of Doors And Windows (Perdaw) which provides a baseline for different classification problems with varying complexity. We investigate the performance of three machine learning models in distinguishing different types of doors and windows in their plan and elevation views. Our findings show that Inception V3 slightly outperforms MobileNet V2, which suggests that the latter solves the same classification tasks with less computational resources with only a minimal compromise in accuracy. Among the three investigated models, ResNet50 yields the lowest quality metrics within a small margin. Overall, all models perform better at classifying building components in their elevation views compared to their plan views. We consistently observed that the models yield the best results with 100{\%} accuracy for the binary classification problems, and dropped to close to 70{\%} accuracy for the 40-class classification problems.
OriginalsprogEngelsk
TitelEngineering Applications of Neural Networks
RedaktørerLazaros Iliadis , Ilias Maglogiannis , Antonios Papaleonidas , Elias Pimenidis , Chrisina Jayne
Antal sider12
ForlagSpringer Nature Switzerland
Publikationsdatojun. 2024
Sider288-300
ISBN (Trykt)978-3-031-62494-0
ISBN (Elektronisk)978-3-031-62495-7
DOI
StatusUdgivet - jun. 2024
BegivenhedInternational Conference on Engineering Applications of Neural Networks - Corfu, Grækenland
Varighed: 27 jun. 202430 jun. 2024
https://eannconf.org/2024/

Konference

KonferenceInternational Conference on Engineering Applications of Neural Networks
Land/OmrådeGrækenland
ByCorfu
Periode27/06/202430/06/2024
Internetadresse
NavnCommunications in Computer and Information Science
Vol/bind2141
ISSN1865-0929

Fingeraftryk

Dyk ned i forskningsemnerne om 'Towards Digitisation of Technical Drawings in Architecture: Evaluation of CNN Classification on the Perdaw Dataset'. Sammen danner de et unikt fingeraftryk.

Citationsformater