CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

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id ecaadesigradi2019_171
authors Uzun, Can and Çolako?lu, Meryem Birgül
year 2019
title Architectural Drawing Recognition - A case study for training the learning algorithm with architectural plan and section drawing images
source Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 2, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 29-34
summary This paper aims to develop a case study for training an algorithm to recognize architectural drawings. In order to succeed that, the algorithm is trained with labeled pixel-based, architectural drawing (plan and section) dataset. During the training process, transfer learning (pre-training model) is applied. The supervised learning and convolutional neural network are utilized. After certain iterations, the algorithm builds awareness and can classify pixel-based plan and section drawings. When the algorithm is shown a section that is not produced with conventional drawing technic but through hybrid technics, it could predict the drawing class correctly with %80 of accuracy. On the other hand, some of the algorithm prediction is misoriented. We examined this prediction problem in the discussion section. The results illustrate that neural networks are successful in training algorithms to recognize and classify pixel-based architectural drawings. But for a highly accurate algorithm prediction, the dataset of the drawing images must be ordered, according to sample resolution, sample size and sample coherence for the dataset.
keywords Classification Algorithm; Pixel-Based Architectural Drawing Recognition; Plan; Section
series eCAADeSIGraDi
full text file.pdf (4,667,994 bytes)
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100%; open Domingos, Pedro (2015) Find in CUMINCAD The Master Algorithm. How the Quest for the Ultimate Learning Machine will Remake Our World , Basic Books, New York

100%; open Ha, David and Eck, Douglas (2017) Find in CUMINCAD A Neural Representation of Sketch Drawings , arXiv preprint, p. arXiv:1704.03477

100%; open Halevy, Alon and Norvig, Peter (2009) Find in CUMINCAD The Unreasonable Effectiveness of Data , IEEE Computer Society

100%; open Huang, Weixin and Zheng, Hao (2018) Find in CUMINCAD Architectural Drawings Recognition and Generation through Machine Learning , the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA2018), Mexico City

100%; open Kaiyrbekov, Kurmanbek and Sezgin, Metin (2019) Find in CUMINCAD Stroke-based sketched symbol reconstruction and segmentation , arXiv preprint, p. arXiv:1901.03427

100%; open Kesavaraj G K, G and Sukumaran, Surya (2013) Find in CUMINCAD A study on classification techniques in data mining , 2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)

100%; open Lu, Wayne and Tran, Elizabeth (2017) Find in CUMINCAD Free-hand Sketch Recognition Classification , CS 231N Project Report

100%; open Triantafillou, Eleni, Zhu, Tyler, Dumoulin, Vincent, Lamblin, Pascal, Xu, Kelvin, Goroshin, Ross, Gelada, Carles, Swersky, Kevin, Manzagol, Pierre-Antoine and Larochelle, Hugo (2009) Find in CUMINCAD Meta-dataset: A dataset of datasets for learning to learn from few examples , arXiv preprint

100%; open Xu, Peng, Huang, Yongye, Yuan, Tongtong, Pang, Kaiyue, Song, Yi-Zhe, Xiang, Tao, Hospedales, Timothy M., Ma, Zhanyu and Guo, Jun (2018) Find in CUMINCAD SketchMate: Deep Hashing for Million-Scale Human Sketch Retrieval , arXiv preprint

100%; open Yesilbek, Kemal Tugrul and Sezgin, T. Metin (2017) Find in CUMINCAD Sketch Recognition with Few Examples , Computers & Graphics

100%; open Zuo, Huo, Lu, Jie, Zhang, Guangquan and Liu, Feng (2018) Find in CUMINCAD Fuzzy Transfer Learning Using an Infinite Gaussian Mixture Model and Active Learning , IEEE Transactions on Fuzzy Systems, 27(DOI: 10.1109/TFUZZ.2018.2857725), pp. 291-303

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