Cumincad : CUMINCAD References : Search Results

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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	Zhang, Yinda, Shuran Song, Ersin Yumer, Manolis Savva, Joon-Young Lee, Hailin Jin, and Thomas Funkhouser (2017) Physically-Based Rendering for Indoor Scene Understanding Using Convolutional Neural Networks , ArXiv:1612.07429 [Cs], July. http://arxiv.org/abs/1612.07429

	Zhao, P., Fei, Y., Huang, Y., Feng, Y., Liao, W., & Lu, X. (2023) Design-condition-informed shear wall layout design based on graph neural networks , Advanced Engineering Informatics, 58, 102190, https://doi.org/10.1016/j.aei.2023.102190

	Zhao, P., Fei, Y., Huang, Y., Feng, Y., Liao, W., & Lu, X. (2023) Design-condition-informed shear wall layout design based on graph neural networks , Advanced Engineering Informatics, 58, 102190. https://doi.org/10.1016/j.aei.2023.102190

	Zhao, P., Liao, W., Huang, Y., & Lu, X. (2023) Intelligent Beam Layout Design for Frame Structure Based on Graph Neural Networks , Journal of Building Engineering, 63, 15499. Available at: https://doi.org/1.116/j.jobe.222.15499

	Zheng, Q and Zheng, C (2017) NeuroLens: Data-Driven Camera Lens Simulation Using Neural Networks , Computer Graphics Forum, 36(8), pp. 390-401

	Zheng, Y. (2011) Location-based social networks: Users. , Zheng, Y. and Zhou, X. (eds), Computing with Spatial Trajectories, Springer

	Zhong, X., Koh, I. and Fricker, P. (2023) Building-GNN: Exploring a co-design framework for generating controllable 3D building prototypes by graph and recurrent neural networks , eCAADe 2023: Digital Design Reconsidered, Graz, Austria, pp. 431-440. Available at: https://doi.org/10.52842/conf.ecaade.2023.2.431

	Zhong, X., Koh, I., & Fricker, P. D. P. (2023) Building-GNN: Exploring a co-design framework for generating controllable 3D building prototypes by graph and recurrent neural networks , Digital Design Reconsidered: Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023), 431-440. https://doi.org/10.52842/conf.ecaade.2023.2.431

	Zhou, J., Cui, G., Hu, S., Zhang, Z., Yang, C., Liu, Z., Wang, L., Li, C., Sun, M., (2020) Graph neural networks: A review of methods and applications , AI Open 1, 57-81. https://doi.org/https://doi.org/10.1016/j.aiopen.2021.01.001

	Zhou, W. (1999) Verification of the Nonparametric Characteristics of Backpropagation Neural Networks for Image Classifications , IEEE Transactions on Geoscience and Remote Sensing. Vol. 37(2), p. 771-779

	Zitzler, E and Thiele, L, (1998) An evolutionary algorithm for multi-objective optimization: the strength Pareto approach , Technical Report 43, Computer engineering and Communication Networks Laboratory, Swiss Federal Institute of Technology, Zurich, Switzerland

	Zou, AM, Hou, ZG, Fu, SY and Tan, M (2006) Neural networks for mobile robot navigation: a survey , International Symposium on Neural Networks, Berlin, pp. 1218-1226

	Zweig, K. A. (2016) Network Analysis Literacy: A Practical Approach to the Analysis of Networks , Springer-Verlag

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