3、城市作为一个整体，成为未来人居的基础设施 垂直城市 © WOHA WOHA事务所通过把这一平方公里的土地分成一共可以容纳 111111 人的网格,组成了一个“通透的网格城市”。“我们把上千个很小的居住单元放在一个高层聚落里，并不是通过常规的垂直交通工具上下，而是通过所谓的天街，那里每条街都只有十层，你可以走...
In this context, this chapter reflects on a new urban design methodology鈥擠ata Augmented Design (DAD), first proposed in 2015, to highlight the use of data in design. This chapter introduces the profile of DAD by comparing its definition with related concepts such as Planning Support Systems...
以下哪一项不属于数据增强设计(Data Augmented Design,DAD)的特点?A.从社会空间回归物质空间:通过社交网络、兴趣点、人类活动和移动等数据以及定量评价方法作为连接B.感知维度:对应于设计中讲的“场所精神”,“借助新的数据和方法实现望山见水记乡愁”C.设计方法工具化: 设计的方法将会在模型工具中得以体现,定量关系...
以下关于数据增强设计(Data Augmented Design,DAD)的常用方法,哪一个叙述不正确? A、(A) 利用“空间抽象模型”以明确和适当地抽象空间设计,如:空间句法(认知和环境心理)、格网划分法、节点法等 B、(B) 为明确空间的统计学效应,使用各种“空间分析与统计”工具,常见的如:Grasshopper、City Engine等...
当然，label不变/协变只是必要条件，整个数据增广有效的充分必要条件应该是：label不变/协变（取决于任务...
A head-mounted operating binocular for augmented reality visualization in medicine--design and initial evaluation. for maxillofacial surgery =-=[23]-=-, augmentation of magnetic resonance imaging (MRI) data onto an external camera view for neurosurgery [24], and ... W Birkfellner,M Figl,K ...
We show that the improved performance stems from the combination of a deep, high-capacity model and an augmented training set: this combination outperforms both the proposed CNN without augmentation and a “shallow” dictionary learning model with augmentation. Finally, we examine the influence of ...
Interestingly, while the CGCNN-HD trained on augmented data has the lowest testing MAE, the dense region of underpredicted formation energies seen in Fig.3(d) leads to a substantial number of misidentified unstable structures, hindering the model’s ability to filter unstable structures. This will...
We show that the improved performance stems from the combination of a deep, high-capacity model and an augmented training set: this combination outperforms both the proposed CNN without augmentation and a “shallow” dictionary learning model with augmentation. Finally, we examine the influence of ...
domains with very limited data, this could result in further overfitting. Therefore, it is important to consider search algorithms for deriving an optimal subset of augmented data to train Deep Learning models with. More on this topic will be discussed in Design Considerations of Data Augmentation....