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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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40%; open Van de Ven, Cornelis (1987) Find in CUMINCAD Space in Architecture , Assen/Maastricht: Van Gorcum
40%; open Ven, CVD (1987) Find in CUMINCAD Space in Architecture: The Evolution of a New Idea in the Theory and History of the Modern Movements , Van Gorcum
40%; open Yoshitsugu Aoki (1987) Find in CUMINCAD Stochastic one-dimensional discrete space model for urban fire spread: A theoretical analyses on stochastic spread of fire in urban area; Part 1 , Journal of Archit. Plann. Environ. Engng, AIJ, No.381, pp. 111-121
40%; open Alani, M. and Al-Kaseem, B. (2021) Find in CUMINCAD Fill in the Blanks: Deep Convolutional Generative Adversarial Networks to Investigate the Virtual Design Space of Historical Islamic Patterns in Proceedings of the 9th ASCAAD Conference , Cairo, Egypt [Virtual Conference], pp. 614-621. Available at: http://papers.cumincad.org/data/works/att/ascaad2021_093.pdf (Accessed 6 March 2022)
40%; open Arvanitidis G, Hansen L, Hauberg S (2018) Find in CUMINCAD Latent Space Oddity: On the Curvature of Deep Generative Models , ICLR 2018. pp. 1–15
40%; open Chen, J. & Stouffs, R. (2021) Find in CUMINCAD From Exploration to Interpretation-Adopting Deep Representation Learning Models to Latent Space Interpretation of Architectural Design Alternatives , Proceedings of the 26th International Conference of the Association for Computer-Aided Architectural Design Research Asia (CAADRIA) 2021
40%; open Chen, J., & Stouffs, R. (2021) Find in CUMINCAD From Exploration to Interpretation-Adopting Deep Representation Learning Models to Latent Space Interpretation of Architectural Design Alternatives. , The Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), Available at: https://doi.org/1.52842/conf.caadria.221.1.131.
40%; open Hoffman, Stephen J. (2011) Find in CUMINCAD Deep Space Habitat Concept of Operations for Transit Mission Phases. (NASA TM 2012-217369) , Houston, TX: NASA Johnson Space Center
40%; open Jachna, T Santo, Y and Schadewitz, N (2007) Find in CUMINCAD Deep space , International Journal of Architectural Computing, 5(1), 146-160
40%; open Kinugawa, H and Takizawa, A (2019) Find in CUMINCAD Deep Learning Model for Predicting Preference of Space by Estimating the Depth Information of Space using Omnidirectional Images , Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference
40%; open Kinugawa, H. and Takizawa, A. (2019) Find in CUMINCAD Deep Learning Model for Predicting Preference of Space by Estimating the Depth Information of Space using Omnidirectional Images. , Proceedings of ECAADE SIGRADI 2019, Porto, Portugal
40%; open Mostafa A and Al-Kaseem B (2021) Find in CUMINCAD Fill in the blanks: Deep convolutional generative adversarial networks to investigate the virtual design space of historical islamic patterns , 9th ASCAAD Conf Proc 2021: 614–621.
40%; open Okabe, A. (2017) Find in CUMINCAD Dynamic spaces with subjective depth , The public space in monsoon Asia. Kult-ur, 4(7), 151-164. https://doi.org/10.6035/Kult-ur.2017.4.7.6Oki, T., & Kizawa, S. (2021). Evaluating Visual Impressions based on Gaze Analysis and Deep Learning. A Case Study of Attractiveness Evaluation of Streets in Densely Built-up Wooden Residential Area. In The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (pp. 887-894), ISPRS Congress. https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-887-2021
40%; open Qi CR, Yi L, Su H, et al (2017) Find in CUMINCAD Pointnet++: Deep hierarchical feature learning on point sets in a metric space , Advances in Neural Information Processing Systems. 2017;30. arXiv:1706.02413 [cs.CV].
40%; open Qi, C. R., Su, H., Mo, K. & Guibas, L. J. (2017) Find in CUMINCAD PointNet++: Deep hierarchical feature learning on point sets in a metric space , 31st Advances Neural Information Processing Systems (NIPS 2017) (pp. 5099-5108)
40%; open Qi, C. R., Yi, L., Su, H., & Guibas, L. J. (2017) Find in CUMINCAD Pointnet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space , Paper presented at the Advances in Neural Information Processing Systems, 17-December 51-519
40%; open Qi, CR, Yi, L, Su, H and Guibas, LJ (2017) Find in CUMINCAD PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space , Conference on Neural Information Processing Systems (NIPS) 2017
40%; open Wang, L., Han, X., He, J., & Jung, T. (2022) Find in CUMINCAD Measuring residents perceptions of city streets to inform better street planning through deep learning and space syntax , ISPRS Journal of Photogrammetry and Remote Sensing, 190, 215-230. https://doi.org/10.1016/j.isprsjprs.2022.06.011
40%; open Zhang, Fan, Fabio Duarte, Ruixian Ma, Dimitrios Milioris, Hui Lin, and Carlo Ratti (2016) Find in CUMINCAD Indoor Space Recognition using Deep Convolutional Neural Network: A Case Study at MIT Campus , arXiv preprint arXiv:1610.02414
40%; open Zhang, Fan, Fabio Duarte, Ruixian Ma, Dimitrios Milioris, Hui Lin, and Carlo Ratti (2016) Find in CUMINCAD Indoor Space Recognition using Deep Convolutional Neural Network: A Case Study at MIT Campus , arXiv preprint arXiv:1610.02414

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