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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	Ameijde JV and Song Y. (2018) Data-driven urban porosity: incorporating parameters of public space into a generative urban design Process , 23rd international conference on computer-aided architectural design research in Asia: learning, prototyping and adapting, CAADRIA 2018. The association for computer-aided architectural design research in Asia (CAADRIA), Beijing, China, 17–19 May 2018, pp. 173–182. Hong Kong: The Association of Computer-Aided Architectural Design Research Asia (CAADRIA)

	Amy Genender-Feltheimer (2018) Visualizing High Dimensional and Big Data , Procedia Computer Science, Cyber Physical Systems andDeep Learning Chicago 140 (January): 112–21

	Ariza I, Mirjan A, Gandia A, et al. (2018) In place detailing , ACADIA, pp. 312–321, http://papers.cumincad.org/data/works/att/acadia18_312.pdf

	As, I., Pal, S. & Basu, P. (2018) Artificial intelligence in architecture: Generating conceptual design via deep learning , International Journal of Architectural Computing, 16(4), 306–327. https://doi.org/10.1177/1478077118800982Bronstein, M. M., Bruna, J., LeCun, Y., Szlam, A., & Vandergheynst, P. (2017). Geometric deep learning: Going beyond Euclidean data. IEEE Signal Processing Magazine, 34(4), 18–42. https://doi.org/10.1109/MSP.2017.2693418

	Barczik, G, Fissabre, A, Hahn, I, KÃ¶nigstein, G, Matcha, H and Roskamm, N (2018) Teaming, taming and teeming: Teaming up people for taming complex problems by creating environments teeming with possibilities , Proceedings of: Research culture in architecture - international conference on cross-disciplinary collaboration

	Bechtel, B., Alexander, P. J., Beck, C., J Böhner. & Yong, X.. (2018) Generating WUDAPT Level 0 data – Current status of production and evaluation , Urban Climate, 27, 24-45. https://doi.org/10.1016/j.uclim.2018.10.001

	Bernstein, Ph (2018) Architecture, Design, Data: Practice Competencies in the Era of Computation , BirkhÃ¤user, Basel

	Bertram A., Othmer C. and Zimmermann R. (2018) Towards Real-time Vehicle Aerodynamic Design via Multi-fidelity Data-driven Reduced Order Modeling , AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, Kissimmee, Florida: American Institute of Aeronautics and Astronautics

	Beyhan, F., & Arslan Selcuk, S. (2018) 3D Printing in Architecture: One Step Closer to a Sustainable Built Environment , Lecture Notes in Civil Engineering, 253–268. https://doi.org/10.1007/978-3-319-63709-9_20Ching-Shun, T. (2006). Smart Structures: Designs with Rapid Prototyping. Progress in Design & Decision Support Systems in Architecture and Urban Planning, 415–429. Retrieved from http://papers.cumincad.org/data/works/att/ddss2006-pb-415.content.pdfDefacto (2016) The Rise Pavilion [Project] Guinness World Record: Largest 3D Printed Structure 2016 Retrieved from https://3dprint.com/147981/defacto-rise-pavilion-guinness/

	Bidgoli A and Veloso P (2018) Deepcloud: the application of a data-driven, generative model in design , ACADIA 2018: Recalibration: On imprecision and infidelity, Universidad Iberoamericana, Mexico City, Mexico, 18–20 October 2018.

	Bidgoli, A. V. (2018) DeepCloud , The Application of a Data-driven, Generative Model in Design. In ACADIA 2018: Recalibration (pp. 176-185). ACADIA

	Bidgoli, Ardavan, and Pedro Veloso (2018) DeepCloud. The Application of a Data-driven, Generative Model in Design , ACADIA 2018: Recalibration: On Imprecision and Infidelity [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA)], Mexico City, Mexico, 18–20 October 2018, edited by P. Anzalone, M. del Signore, and A. J. Wit, 176–185. CUMINCAD

	Birgonul, Z, Cocho-Bermejo, A and Sarrablo, V (2018) Symbiotic Data Platform , Responsive Cities Symposium: Active Public Space 2017, Barcelona: Institute for Advanced Architecture of Catalonia., pp. 89-97

	Bobo Zhao, Zhu Wang, Zhiwen Yu, and Bin Guo (2018) EmotionSense: Emotion recognition based on wearable wrist[1]band , 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/ CBDCom/IOP/SCI), 346–355

	Bonczak, B. & Kontokosta, C.E. (2019) Large-scale parameterization of 3D building morphology in complex urban landscapes using aerial LiDAR and city administrative data , Computers, Environment and Urban Systems, 73pp. 126-142. doi.org/10.1016/j.compenvurbsys.2018.09.004

	Borrmann, A, König, M, Koch, C and Beetz, J (2018) Building Information Modeling: Why? What? How? , Springer

	Borrmann, A., Konig, M., Koch, C., And Beetz, J. (2018) Building Information Modeling: Why? What? How? , Building Information Modeling. Springer, Cham. Available at: https://doi.org/1.17/978-3-319-92862-31

	Broos, T., Verbert, K., Langie, G., Van Soom, C., & De Laet, T. (2018) Low-Investment, Realistic-Return Business Cases for Learning Analytics Dashboards: Leveraging Usage Data and Microinteractions , 13th European Conference on Technology Enhanced Learning, EC-TEL 2018 (Vol. 11082 LNCS, pp. 399-405): Springer Verlag

	Buxton, Pamela (eds) (2018) Metric Handbook: Planning and Design Data (Sixth Edition Published) , Taylor and Francis, London

	Cai BY, Li X, Seiferling I, et al (2018) Treepedia 2.0: applying deep learning for large-scale quantification of urban tree cover , 2018 IEEE International Congress on Big Data (BigData Congress), San Francisco, CA, USA, 2-7 July

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