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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	Sultana, Farhana, Abu Sufian, and Paramartha Dutta (2020) Evolution of Image Segmentation Using Deep Convolutional Neural Network: A Survey , Knowledge-Based Systems 201–202: 106062. https://doi.org/https://doi.org/10.1016/j.knosys.2020.106062

	Tan, H. et al. (2020) Building envelope integrated green plants for energy saving , Energy Exploration & Exploitation, 38(1), pp. 222-234. Available at: https://doi.org/10.1177/0144598719875529

	Thompson, R, Ghalebi, E, DeVries, T and Taylor, GW (2020) Building LEGO Using Deep Generative Models of Graphs , arXiv preprint arXiv:2012.11543, 2012, pp. 1-12

	Ulyanov D, Vedaldi A and Lempitsky V (2020) Deep Image Prior , Int J Comput Vis 2020; 128: 1867–1888.

	Wang, S., Liu, C., Zhang, G., Luo, Q., Xu, W., & Raspall, F. (2020) Digital Planting-Fabrication of Integrated Concrete Green Wall via Additive Manufacturing , RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference, Vol 1, pp145-151. https://doi.org/10.52842/conf.caadria.2020.1.145

	Wang, S., Zargar, S. A. & Yuan, F.-G. (2020) Augmented reality for enhanced visual inspection through knowledge-based deep learning , Structural Health Monitoring, 20(1), 426-442

	Wilaiprasitporn, T., Ditthapron, A., Matchaparn, K., Tongbuasirilai, T., Banluesombatkul, N., & Chuangsuwanich, E. (2020) Affective EEG-Based Person Identification Using the Deep Learning Approach , Ieee Transactions on Cognitive and Developmental Systems, 12(3), 486-496. https://doi.org/10.1109/tcds.2019.2924648

	Wu, X., Sahoo, D., Hoi, S.C.H., (2020) Recent advances in deep learning for object detection , Neurocomputing 396, 39-64. https://doi.org/10.1016/j.neucom.2020.01.085

	Xi, F, Guangcai, G, Guannan, L, Liang, C, Weiqiang, L & Pei, P. (2021) A hybrid deep transfer learning strategy for short term cross-building energy prediction , Energy, 215, 119-208. https://doi.org/10.1016/j.energy.2020.119208

	Yi, YK, Zhang, Y and Myung, J (2020) House style recognition using deep convolutional neural network , AUTOMATION IN CONSTRUCTION, 118, p. 103307

	Yousif, S., & Bolojan, D. (2021) Deep-Performance: Incorporating Deep Learning for Automating Building Performance Simulation in Generative Systems , 26th International Conference on Computer-Aided Architectural Design ResearchAsia: Projections, CAADRIA 2020 (pp. 151-160). The Association for Computer-Aided Architectural Design ResearchAsia (CAADRIA)

	Zhang X, Han L, Han L, et al (2020) How well do deep learning-based methods for land cover classification and object detection perform on high resolution remote sensing imagery? , Remote Sens 2020; 12: 417

	Zhang, Z, Cui, P and Zhu, W (2020) Deep learning on graphs: A survey , IEEE Transactions on Knowledge and Data Engineering

	Zhen H., Wei Y. & Gang L. (2020) A performance-based urban block generative design using deep reinforcement learning and computer vision , The International Conference on Computational Design and Robotic Fabrication,pages 134–143. Springer

	Helbich, M., Yao, Y., Liu, Y., Zhang, J., Liu, P., & Wang, R. (2019) Using deep learning to examine street view green and blue spaces and their associations with geriatric depression in Beijing, China , Environment International, 126, 107-117

	Ki, D. and Lee, S. (2021) Analyzing the effects of Green View Index of neighborhood streets on walking time using Google Street View and deep learning , Landscape and Urban Planning, 205, p. -

	Ki, D., & Lee, S. (2021) Analyzing the Effects of Green View Index of Neighborhood Streets on Walking Time Using Google Street View and Deep Learning , Landscape and Urban Planning, 25, 1392. Available at: https://doi.org/1.116/j.landurbplan.22.1392

	A Blaney (2020) Designing Parametric Matter: Exploring adaptive self-assembly through tuneable environments , PhD thesis, LancasterUniversity

	A Mahdavi (2020) In the matter of simulation and buildings: some critical reflections , Journal of Building Performance Simulation 13 (1): 26–33

	A. Anton, A. Jipa, L. Reiter, and B. Dillenburger (2020) Fast Complexity: Additive Manufacturing for Prefabricated Concrete Slabs , DigitalConcrete 2020; Paper Proceedings of the Second RILEM InternationalConference on Concrete and Digital Fabrication. Cham: Springer. 1067–77.

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