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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	Shimizu, R. (2016) Deep Learning Programming , Technological Review Co., Ltd., Tokyo

	Abe, H, et al. (2016) Possibility of applying deep learning to the evaluation of street scape , Proceeding of the annual symposium of Japan Society of Graphic Science, pp. 85-90

	Boulch, A and Marlet, R (2016) Deep Learning for Robust Normal Estimation in Unstructured Point Clouds , Proceeding of SGP 2016, Berlin, pp. 281-290

	Caley, Jeffrey A., Nicholas R.J. Lawrance, and Geoffrey A. Hollinger (2016) Deep Learning of Structured Environments for Robot Search , Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 3987–92. Daejeon, Korea: IROS. doi:10.1109/IROS.2016.7759587

	Dubey, A, Naik, N, Parikh, D, Raskar, R and Hidalgo, CA (2016) Deep learning the city: Quantifying urban perception at a global scale , European conference on computer vision, pp. 196-212

	Dubey, A., Naik, N., Parikh, D., Raskar, R. & Hidalgo, C. A. (2016) Deep Learning the City: Quantifying Urban Perception at a Global Scale , B. Leibe, J. Matas, N. Sebe, & M. Welling (Eds.), Computer Vision – ECCV 2016 (pp. 196–212). Springer International Publishing. https://doi.org/10.1007/978-3-319-46448-0_12

	Dubey, A., Naik, N., Parikh, D., Raskar, R. & Hidalgo, C. A. (2016) Deep Learning the City: Quantifying Urban Perception at a Global Scale , Computer Vision – ECCV 2016 Lecture Notes in Computer Science, 196-212. doi:10.1007/978-3-319-46448-0_12

	Dubey, A., Naik, N., Parikh, D., Raskar, R., & Hidalgo, C. A. (2016) Deep Learning the City: Quantifying Urban Perception At a Global Scale , European Conference on Computer Vision, 196-212

	Dubey, A., Naik, N., Parikh, D., Raskar, R., & Hidalgo, C. A. (2016) Deep Learning the City: Quantifying Urban Perception at a Global Scale , B. Leibe, J. Matas, N. Sebe, & M. Welling (Eds.), Computer Vision - ECCV 2016 (pp. 196-212). Springer International Publishing. https://doi.org/10.1007/978-3-319-46448-0_12

	Dubey, Abhimanyu, Nikhil Naik, Devi Parikh, Ramesh Raskar, and César A. Hidalgo (2016) Deep Learning the City: Quantifying Urban Perception at a Global Scale , European Conference on Computer Vision, pp. 196-212. Cham: Springer

	Dumoulin, V., & Visin, F. (2016) A guide to convolution arithmetic for deep learning , ArXiv:1603.07285 [Cs, Stat]. http://arxiv.org/abs/1603.07285

	Gal, Y and Ghahramani, Z (2016) Dropout as a bayesian approximation: Representing model uncertainty in deep learning , international conference on machine learning, pp. 1050-1059

	Goodfellow I, Bengio Y and Courville A. (2016) Deep learning. , Cambridge: The MIT Press.

	Goodfellow I, Bengio Y, and Courville A (2016) Deep Learning , Cambridge: MIT Press, p. 45

	Goodfellow I, Bengio Y, Courville A, et al (2016) Deep learning , Cambridge, MA: MIT Press, 2016

	Goodfellow I., Y. Bengio, and A. Courville. (2016) Deep Learning , Cambridge, MA: The MIT Press

	Goodfellow, I, Bengio, Y and Courville, A (2016) Deep learning , MIT press

	Goodfellow, I, Bengio, Y and Courville, A (2016) Deep Learning , MIT Press, Cambridge

	Goodfellow, I, Bengio, Y and Courville, A (2016) Deep Learning , MIT Press

	Goodfellow, I, Bengio, Y and Courville, A (2016) Deep Learning , MIT

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