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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	Agnello, F. (2022) Perspective restitution from view cameras photos , The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 46, 17-24

	Pang HE and Biljecki F (2022) 3D building reconstruction from single street view images using deep learning , International Journal of Applied Earth Observation and Geoinformation. 2022;112:102859

	Pang, H. E., & Biljecki, F. (2022) 3D building reconstruction from single street view images using deep learning , International Journal of Applied Earth Observation and Geoinformation, 112, 102859

	Wang, R., Browning, M. H. E. M., Qin, X., He, J., Wu, W., Yao, Y., & Liu, Y. (2022) Visible green space predicts emotion: Evidence from social media and street view data , Applied Geography, 148, 102803. https://doi.org/10.1016/j.apgeog.2022.102803

	Zhang, L., Zhang, L., & Liu, X. (2022) Evaluation of Urban Spatial Growth Performance from the Perspective of a Polycentric City: A Case Study of Hangzhou , Land, 11(8). https://doi.org/10.3390/land11081173

	Zhang, Y., Zhang, Q., Zhao, Y., Deng, Y., & Zheng, H. (2022) Urban Spatial Risk Prediction and Optimization Analysis of Poi Based on Deep Learning from the Perspective of an Epidemic , International Journal of Applied Earth Observation and Geoinformation, 112, 12942. Available at: https://doi.org/1.116/j.jag.222.12942

	Bhatla, A, Choe, SY, Fierro, O and Leite, F (2012) Evaluation of accuracy of as-built 3D modeling from photos taken by handheld digital cameras , Automation in Construction, 28, pp. 116-127

	Agarwal, R., Chandrasekaran, S., & Sridhar, M. (2020) Imagining construction's digital future , McKinsey & Company. Retrieved January 15, 2022, from https://www.mckinsey.com/business-functions/operations/our-insights/imagining-constructions-digital-future

	Aryal, J., Sitaula, C., & Aryal, S. (2022) Ndvi Threshold-based Urban Green Space Mapping from Sentinel-2a At the Local Governmental Area (lga) Level of Victoria, Australia , Land, 11(3), 351. Available at: https://doi.org/1.339/land113351

	Bhandari, T. (2021) What makes an mrna vaccine so effective against severe COVID-19? , Washington University School of Medicine in St. Louis. Retrieved March 2022, from https://medicine.wustl.edu/news/what-makes-an-mrna-vaccine-so-effective-against-severe-covid-19/#:~:text=In%20clinical%20trials%2C%20both%20were,considered%20for%20 emergency%20use%20 authorization.

	Bielski, J., Mete, B., Eisenstadt, V., Langenhan, C., Petzold, F., Dengel, A., & Althoff, K.D. (2022) Chasing the White Rabbit - A case study of predicting design phases of architects by training a deep neural network with sketch recognition through a digital drawing board , Proceedings of International Conferences on Computational Creativity. Association for Computational Creativity. Retrieved August 29, 2022 from https://computationalcreativity.net/iccc22/wp-content/uploads/2022/06/ICCC-2022_1S_Bielski-et-al..pdf

	Boeing, G. (2017) OSMnx: New methods for acquiring, constructing, analyzing, and visualizing complex street networks , Computers, Environment and Urban Systems, 65, 126–139. https://doi.org/10.1016/j.compenvurbsys.2017.05.004Chestnut, J. (2018, March 28). Pedestrians first: Tools for a Walkable City. Institute for Transportation and Development Policy. Retrieved February 3, 2022, from https://www.itdp.org/publication/walkability-tool/

	Bolojan, D. (2022) From Artificial to Architectural Intelligence , N. Leach & M. del Campo (Eds.), Machine Hallucinations: Architecture and Artificial Intelligence: Wiley

	Chaillou S (2022) Artificial intelligence and architecture: from research to practice , Basel: De Gruyter: Birkhaaser, 2022

	Chaillou S. (2019) The Advent of Architectural AI , A Historical Perspective. Towards Data Science.[Online] Available at:https://towardsdatascience.com (Accessed:05 Jan 2022)

	Chen Y, Lu Y, Gu T, Bian Z, Wang L and Tong Z. (2022) From Separation to Incorporation - A Full-Circle Application of Computational Approaches to Performance-Based Architectural Design , Springer Singapore, pp. 189–198, ISBN: 9789811659836. https://doi.org/10.1007/978-981-16-5983-6.

	Chen, C., Li, H., Luo, W., Xie, J., Yao, J., Wu, L. and Xia, Y. (2022) Predicting the effect of street environment on residents mood states in large urban areas using machine learning and street view images , Science of The Total Environment, 816, p.151605

	Chen, W., Zhang, J., Liu, S., Liang, S., Zhang, Y., & Fu, S. (2023) The spatial configuration of buildings: A vital consideration impossible to ignore in regulating urban land surface temperature? Evidence from 35 Chinese cities , Science of The Total Environment, 865, 160946. https://doi.org/10.1016/j.scitotenv.2022.160946

	Chen, Y., Lu, Y., Gu, T., Bian, Z., B, L. W. & Tong, Z. (2022) From Separation to Incorporation - A Full-Circle Application of Computational Approaches to Performance-Based Architectural Design , Proceedings of the 2021 DigitalFUTURES (pp. 189–198). https://doi.org/10.1007/978-981-16-5983-6

	Chen, Y., Lu, Y., Gu, T., Bian, Z., B, L. W., & Tong, Z. (2022) From Separation to Incorporation - A Full-Circle Application of Computational Approaches to Performance-Based Architectural Design , Proceedings of the 2021 DigitalFUTURES (pp. 189-198). Springer Singapore

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