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Autore: | Yuan Philip F |
Titolo: | Proceedings of the 2021 DigitalFUTURES : The 3rd International Conference on Computational Design and Robotic Fabrication (CDRF 2021) / / editors, Philip F. Yuan [et al.] |
Pubblicazione: | Singapore, : Springer Singapore Pte. Limited, 2021 |
Descrizione fisica: | 1 online resource (401 p.) |
Soggetto topico: | Automatic control engineering |
Computer-aided design (CAD) | |
Artificial intelligence | |
Soggetto non controllato: | History, Theory and Critics of Building Technology |
Performance-based Design | |
Fabrication and Construction | |
Data Mining and Visualizing | |
Immersive and Interactive Environment | |
Architectural Intelligence | |
Open Access | |
Altri autori: | YuanPhilip F ChaiHua YanChao LeachNeil |
Note generali: | Description based upon print version of record. |
Nota di contenuto: | Intro -- Preface -- Organization -- Committees -- Honorary Advisors -- Organization Committees -- Scientific Committees -- Contents -- Computation and Formation -- Serlio and Artificial Intelligence: Problematizing the Image-to-Object Workflow -- 1 Influence of the Disciplinary Treatise -- 2 Analogical and Digital Flux -- 3 Analog-to-Digital Information Processing -- 4 Problematizing the Image-to-Object Workflow -- 5 Operative Model: Portico -- 5.1 Intelligence Beyond Serlio -- References -- A Generative Approach to Social Ecologies in Project [Symbios]City -- 1 Introduction |
2 Topological Optimization as a Method of Parametric Semiology -- 2.1 Background -- 2.2 TO Software and Its Potential to Achieve Tower Semiology -- 2.3 Benchmark Post Processing and Materialization -- 3 Ground Design and Flood Simulation -- 3.1 Flood Simulation -- 3.2 Tower Arrangement -- 3.3 Podium Design and Network Theory -- 4 From Programmatic Distribution to Neighborhood Ecologies -- 4.1 Typical Program Classification and Distribution -- 4.2 Dynamic Programs and Micro-structures -- 5 Façade Development and Sunlight Optimization -- 6 Conclusion -- References | |
Using CycleGAN to Achieve the Sketch Recognition Process of Sketch-Based Modeling -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Network Architecture -- 3.2 Data Preparation -- 3.3 Training Process -- 4 Results -- 4.1 Recognition of Sketch and Generation of Corresponding Building Image -- 4.2 Sketch Reconstruction -- 4.3 Building Images to Sketches -- 5 Conclusion and Discussion -- References -- Exploration on Machine Learning Layout Generation of Chinese Private Garden in Southern Yangtze -- 1 Introduction -- 2 Background -- 3 Research Method -- 3.1 Network Architecture | |
3.2 Dataset -- 3.3 Processing and Labelling Based on Analysis -- 4 Training and Analysis -- 4.1 First Training -- 4.2 Second Training -- 4.3 Third Training -- 4.4 Result Analysis -- 5 Discussion -- References -- Command2Vec: Feature Learning of 3D Modeling Behavior Sequence-A Case Study on "Spiral-stair" -- 1 Introduction -- 2 Related Work -- 3 Methodologies -- 3.1 Data Preparing -- 3.2 Embedding -- 3.3 Command2Vec -- 3.4 Clustering -- 4 Experiment -- 5 Results -- 5.1 Experiment Results -- 5.2 Evaluation -- 6 Conclusion and Discussion -- References | |
Exploring in the Latent Space of Design: A Method of Plausible Building Facades Images Generation, Properties Control and Model Explanation Base on StyleGAN2 -- 1 Introduction -- 2 Related Work -- 2.1 Image Generation Research via GAN in Computer Science -- 2.2 Plan Drawing Generation Research -- 2.3 Building Facades and Other Perspective Architectural Images Generation Research -- 3 Methodology -- 3.1 Training Building Facades Generation Model by StyleGAN2 -- 3.2 Exploration and Explanation of Latent Space -- 3.3 High-Level Prosperity Control | |
3.4 Project Novel Image into Existing Model Instance | |
Sommario/riassunto: | This open access book is a compilation of selected papers from 2021 DigitalFUTURES—The 3rd International Conference on Computational Design and Robotic Fabrication (CDRF 2021). The work focuses on novel techniques for computational design and robotic fabrication. The contents make valuable contributions to academic researchers, designers, and engineers in the industry. As well, readers encounter new ideas about understanding material intelligence in architecture. |
Titolo autorizzato: | Proceedings of the 2021 DigitalFUTURES |
ISBN: | 981-16-5983-4 |
Formato: | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 9910500587003321 |
Lo trovi qui: | Univ. Federico II |
Opac: | Controlla la disponibilità qui |