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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	Isola P, Zhu JY, Zhou T, et al (2018) Image-to-Image translation with conditional adversarial networks , Technical Report arXiv:1611.07004, arXiv, 2018.

	Isola, P, Zhu, J.Y, Zhou, T and Efros, A.A (2018) Image-to-Image Translation with Conditional Adversarial Networks , arXiv:2018

	Isola, P., Zhu, J.-Y., Zhou, T., & Efros, A. A. (2018) Image-to-Image Translation with Conditional Adversarial Networks , ArXiv:1611.07004 [Cs]. http://arxiv.org/abs/1611.07004

	Isola, Phillip, Jun-Yan Zhu, Tinghui Zhou, and Alexei A. Efros (2018) Image-to-Image Translation with Conditional Adversarial Networks , ArXiv:1611.07004 [Cs], November. http://arxiv.org/abs/1611.07004

	Ji, S., Wei, S., & Lu, M. (2019) Fully Convolutional networks for multi-source building extraction from an open aerial and satellite imagery data Set , IEEE Transactions on Geoscience and Remote Sensing, 57(1), 574-586. Scopus. https://doi.org/10.1109/TGRS.2018.2858817on 3D Vision, 3DV 2018, 728-737

	Khean, N, Kim, L, Martinez, J, Doherty, B, Fabbri, A, Gardner, N and Haeusler, M H (2018) The Introspection of Deep Neural Networks - Towards Illuminating the Black Box , Proceedings of CAADRIA 2018, Beijing, pp. 237-246

	Khean, N, Kim, L, Martinez, J, Doherty, B, Fabbri, A, Gardner, N and Haeusler, M. H. (2018) The Introspection of Deep Neural Networks - Towards Illuminating the Black Box , Proceedings of CAADRIA 2018, Beijing, pp. 237 - 246

	Khean, N, Lucas, K, Martinez, J, Doherty, B, Fabbri, A, Gardner, N and Haeusler, HH (2018) The Introspection of Deep Neural Networks: Towards Illuminating the Black Box , Conference: Learning, Adapting and Prototyping - 23rd International Conference of the Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), 2, pp. 237-246

	Khean, N., Kim, L., Martinez, J., Doherty, B., Fabbri, A., Gardner, N. and Haeusler, M.H. (2018) The Introspection of Deep Neural Networks - Towards Illuminating the Black Box - Training Architects Machine Learning via Grasshopper Definitions , Proceedings of the 23rd International Conference of the Association for Computer-Aided Architectural Design Research in Asia (CAADRIA) 2018, Volume 2, Beijing, pp. 237-246

	Kirkley, A, Barbosa, H, Barthelemy, M and Ghoshal, G (2018) From the betweenness centrality in street networks to structural invariants in random planar graphs , Nature Communications, 9(1), p. 2501

	Kvochick, T (2018) Sneaky Spatial Segmentation. Reading architectural drawings with Deep neural networks and without labeling data , Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture, Mexico City, Mexico

	Kvochick, T. (2018) Sneaky Spatial Segmentation. Reading Architectural Drawings with Deep Neural Networks and Without Labeling Data , Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA)

	Kvochick, T. (2018) Sneaky Spatial Segmentation. Reading architectural drawings with Deep neural networks and without labeling data. , Proceedings of ACADIA 2018, Mexico City, Mexico

	Kvochick, Tyler (2018) Sneaky Spatial Segmentation. Reading Architectural Drawings with Deep Neural Networks and Without Labeling Data , 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, 166–175. CUMINCAD.

	Liu, X., Kong, X., Liu, L., & Chiang, K. (2018) Treegan: Syntax-aware Sequence Generation with Generative Adversarial Networks , 218 IEEE International Conference on Data Mining (ICDM) (pp.114-1145)

	Liu, Y., Colburn, A. & Mehlika, I., (2018) Computing Long-term Daylighting Simulations from High Dynamic Range Imagery Using Deep Neural Networks , S.l., s.n

	Ma, Shuang, Jianlong Fu, Chang Wen Chen, and Tao Mei (2018) DA-GAN: Instance-Level Image Translation by Deep Attention Generative Adversarial Networks (with Supplementary Materials , http://arxiv.org/abs/1802.06454

	Marshall, S, Gil, J, Kropf, K, Tomko, M and Figueiredo, L (2018) Street Network Studies: from Networks to Models and their Representations , Networks and Spatial Economics, 18(735), pp. 1-15

	Masters, Dominic, and Carlo Luschi (2018) Revisiting Small Batch Training for Deep Neural Networks , ArXiv:1804.07612 [Cs, Stat], April. http://arxiv.org/abs/1804.07612

	Mehaffy, M, Kryazheva, Y, Rudd, A and Salingaros, N (2018) A Pattern Language for Growing Regions: Places, Networks, Processes. A Collection of 80 Patterns for a New Generation of Urban Challenges , Sustasis Press

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