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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	Yuhao Kang, Fan Zhang, Wenzhe Peng, Song Gao, Jinmeng Rao, Fabio Duarte, and Carlo Ratti (2020) Understanding House Price Appreciation Using Multi-Source Big Geo-Data and Machine Learning , Land Use Policy 111: 104919. https://doi.org/10.1016/j. landusepol.2020.104919

	Yunqin Li, Nobuyoshi Yabuki, and Tomohiro Fukuda (2022) Exploring the Association between Street Built Environment and Street Vitality Using Deep Learning Methods , Sustainable Cities and Society 79(April): 103656

	Z Shaghaghian. and W. Yan (2019) Application of Deep Learning in Generating Desired Design Options: Experiments Using Synthetic Training Dataset , ArXiv Preprint

	Zaghloul M. (2017) Machine-Learning aided Architectural Design , PhD thesis, ETH Zürich, Zürich

	Zaghloul, Mohamed (2015) Machine-Learning Aided Architectural Design: Self-Organizing Map Generate in between Design Alternatives , Proceedings of the 18th Generative Art Conference, 283–93. Venice: GA

	Zamir, AR, Alexander, D and Mubarak, S (2011) Street view challenge: Identification of commercial entities in street view imagery , 2011 10th International Conference on Machine Learning and Applications and Workshops, Honolulu, HI, USA, pp. 380-383

	Zandavali, B (2018) Automated Brick Pattern Generator for Robotic Assembly using Machine Learning and Images , Master's Thesis, University College London

	Zandavali, B.A. and García, M.J. (2019) Automated Brick Pattern Generator for Robotic Assembly using Machine Learning and Images. , Proceedings of ECAADE SIGRADI 2019, Porto, Portugal

	Zavoleas, Y (2015) The Model and Its Operative Significance in Architecture. Objects Driving Evolution in Design Research , Living and Learning: Research for a Better Built Environment: 49th International Conference of the Architectural Science Association, Melbourne, p. 1065-1074

	Zeng, D. and Sycara, K. (1997) Benefits of Learning in Negotiation , Proceedings of the National Conference on Artificial Intelligence (AAAI-97), American Association for Artificial Intelligence, pp. 36–41

	Zeng, D. and Sycara, K. (1998) Bayesian Learning in Negotiation , International Journal of Human-Computer Studies 48, pp. 125–141

	Zhang F, Zhou B, Liu L, et al (2018) Measuring human perceptions of a large-scale urban region using machine learning , Landscape Urban Plann 2018; 180: 148–160.

	Zhang H and Blasetti E (2020) 3D architectural form style transfer through machine learning , RE: anthropocene, proceedings of the 25th international conference of the association of computer-aided architectural design research in Asia, August, 2020, Bangkok. HongKong, pp. 659–668.

	Zhang H and Huang Y (2021) Machine learning aided 2D-3D architectural form finding at high resolution , PF Yuan, J Yao, C Yan et al. (eds) Proceedings of the 2020 DigitalFUTURES. CDRF 2020. Singapore: Springer, 2021, DOI: 10.1007/978-981-33-4400-6_15 372 International Journal of Architectural Computing 21(2)

	Zhang H (2019) 3D model generation on architectural plan and section training through machine learning , Technologies 2019; 7(4): 82, DOI: 10.3390/technologies7040082

	Zhang, F. et al., (2018) Measuring human perceptions of a large-scale urban region using machine learning , Landscape and Urban Planning, Volume 180, pp. 148-160

	Zhang, F., Zhou, B., Liu, L., Liu, Y., Fung, H. H., Lin, H., & Ratti, C. (2018) Measuring Human Perceptions of a Large-scale Urban Region Using Machine Learning , Landscape and Urban Planning, 18, 148-16. Available at: https://doi.org/1.116/j.landurbplan.218.8.2

	Zhang, F., Zhou, B., Liu, L., Liu, Y., Fung, H. H., Lin, H., & Ratti, C. (2018) Measuring human perceptions of a large-scale urban region using machine learning , Landscape and Urban Planning, 180, 148-160

	Zhang, F., Zhou, B., Liu, L., Liu, Y., Fung, H. H., Lin, H., & Ratti, C. (2018) Measuring Human Perceptions of a Large-scale Urban Region Using Machine Learning , Landscape and Urban Planning (pp. 148-16). Available at: https://doi.org/1.116/j.landurbplan.218.8.2

	Zhang, F., Zhou, B., Liu, L., Liu, Y., Fung, H. H., Lin, H., & Ratti, C. (2018) Measuring human perceptions of a large-scale urban region using machine learning , Landscape and Urban Planning, 180, 148-160. https://doi.org/10.1016/j.landurbplan.2018.08.020

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