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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	Han, Z., Yan, W. and Liu, G. (2021) A Performance-Based Urban Block Generative Design Using Deep Reinforcement Learning and Computer Vision , P.F. Yuan et al. (eds) Proceedings of the 2020 DigitalFUTURES. Singapore: Springer Singapore, pp. 134-143

	Hanocka R and Liu H-TD (2021) An introduction to deep learning on meshes , ACM SIGGRAPH 2021 Courses. New York, NY, USA: Association for Computing Machinery, pp. 1–27.

	He, J. & Zheng, H. (2021) Prediction of crime rate in urban neighborhoods based on machine learning , Engineering Applications of Artificial Intelligence, 106, 104460

	He, J., & Zheng, H. (2021) Prediction of Crime Rate in Urban Neighborhoods Based on Machine Learning , Engineering Applications of Artificial Intelligence, 16, 1446. Available at: https://doi.org/1.116/j.engappai.221.1446

	He, J., & Zheng, H. (2021) Prediction of Crime Rate in Urban Neighborhoods Based on Machine Learning , Engineering Applications of Artificial Intelligence. Volume 16, 1446. Available at: https://doi.org/1.116/j.engappai.221.1446.

	He, X., Grassi, G. & Paoletti, I. (2021) Geometric Deep Learning: Prediction of Shape-Shifting Textiles , 12th Annual Symposium on Simulation for Architecture and Urban Design (SimAUD): Human+, SimAUD 2021. The Symposium on Simulation for Architecture and Urban Design (SimAUD)

	He, Y., Liu, X. H., Mei, Y., Schnabel, M. A., Zhang, H, L., Zhao, F. Y. & Zheng, W. (2021) Hybrid framework for rapid evaluation of wind environment around buildings through parametric design, CFD simulation, image processing and machine learning , Sustainable Cities and Society, 73, Article 103092. https://www.sciencedirect.com/science/article/abs/pii/S2210670721003759

	Hoang, N.-D., & Tran, X.-L. (2021) Remote Sensing-Based Urban Green Space Detection Using Marine Predators Algorithm Optimized Machine Learning Approach , Mathematical Problems in Engineering, 2021, 1-22. https://doi.org/10.1155/2021/5586913

	Hoxha, E., Maierhofer, D., Saade, M. R. M., & Passer, A. (2021) Home , Inter-national Journal of Life Cycle Assessment, 26(5), 852-863. https://doi.org/10.1007/s11367-021-01919-9

	Hu, E.J. et al. (2021) LoRA: Low-Rank Adaptation of Large Language Models , International Conference on Learning Representations

	Huang, Y., Lu, X., Sun, C., Zhang, F., Zhao, P. & Zhao, X. (2021) Automated Simulation Framework for Urban Wind Environments Based on Aerial Point Clouds and Deep Learning , Remote Sensing, 13(12), 2383#. https://www.mdpi.com/2072-4292/13/12/2383#

	Ji, S., Pan, S., Cambria, E., Marttinen, P., & Yu, P. S. (2022) A Survey on Knowledge Graphs: Representation, Acquisition, and Applications , IEEE Transactions on Neural Networks and Learning Systems, 33(2), 494-514. https://doi.org/10.1109/TNNLS.2021.3070843

	Jia, C., Yang, Y., Xia, Y., Chen, Y.-T., Parekh, Z., Pham, H., Le, Q., Sung, Y.-H., Li, Z., & Duerig, T. (2021) LoRA: Low-Rank Adaptation of Large Language Models , Proceedings of the 38th International Conference on Machine Learning, 4904-4916. https://proceedings.mlr.press/v139/jia21b.html

	Jiangyan, L, Qing, Z, Xin, L, Guannan, L, Zhongming, L, Yi, X, Kuining, L & Bin, L. (2021) Transfer learning-based strategies for fault diagnosis in building energy systems , Energy and Buildings, 250, 111256. https://doi.org/10.1016/j.enbuild.2021.111256

	Jiaxin Zhang, Tomohiro Fukuda, and Nobuyoshi Yabuki (2021) Development of a City-Scale Approach for Façade Color Measurement with Building Functional Classification Using Deep Learning and Street View Images , ISPRS International Journal of Geo-Information 10 (8): 551

	Jingyi He, and Hao Zheng (2021) Prediction of crime rate in urban neighborhoods based on machine learning , Engineering Applications ofArtificial Intelligence 106 (Nov): 104460

	Johanes, M. & Huang, J. (2021) Self-supervised Visual Feature Learning with Deep Neural Networks: A Survey , Proceedings of the 41st Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA), 134-141. https://doi.org/10.52842/conf.acadia.2021.001

	Kajatin, R., Nalpantidis, L., (2021) Image Segmentation of Bricks in Masonry Wall Using a Fusion of Machine Learning Algorithms , Del Bimbo, A., Cucchiara, R., Sclaroff, S., Farinella, G.M., Mei, T., Bertini, M., Escalante, H.J., Vezzani, R. (Eds.), Pattern Recognition. ICPR International Workshops and Challenges, Lecture Notes in Computer Science. Springer International Publishing, Cham, pp. 446-461. https://doi.org/10.1007/978-3-030-68787-8_33

	Kalyanam, R., & Hoffmann, S. (2021) A Reinforcement Learning-based Approach to Automate the Electrochromic Glass and to Enhance the Visual Comfort , MDPI: Applied Sciences,11(15), 6949. Available at: https://doi.org/1.339/app11156949

	Kaspersen, M. H., Bilstrup, K. K., Petersen, M. G. (2021) The Machine Learning Machine: a Tangible User Interface for Teaching Machine Learning , TEI '21: Proceedings of the Fifteenth International Conference on Tangible, Embedded, and Embodied Interaction, February 221, Salzburg, Austria: ACM. Available at: https://doi.org/1.1145/343524.344638

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