Please select the most similar patent number from A, B, C and D. Which number is?
A shear wall arrangement method and apparatus based on a generative adversarial network. The method comprises: acquiring an architectural design drawing to be processed (S101); extracting key elements from the architectural design drawing, and carrying out filling processing on the key elements by using different colors, so as to generate image features to be inputted (S102); and inputting said image features into a pretrained structural generative adversarial network model and processing same, so as to generate a structural design drawing (S103). Thus, a corresponding shear wall structure design can be quickly output according to a standard floor plane drawing in an architectural design, thereby realizing the quick design of a shear wall structure corresponding to the architectural design.
A: A generative adversarial mechanism and attention mechanism-based standard face generation method, comprising: a dataset design step, constructing, according to database-related annotation data, face code having a plurality of non-limiting factors for a face image, and taking the code and the face image as inputs of a model; a model design and training step, using a generative adversarial mechanism and an attention mechanism to design a corresponding network structure, and using the constructed data pair to perform model training, so as to obtain a network model weight; and a model prediction step, predicting the acquired face image by means of the model. The present invention applies deep learning network technology to standard face generation to generate a colour, front-facing, and standard face image under normal light illumination. The method using a deep learning network is capable of obtaining an accurate standard face photograph, reducing the difficulty of matching with data in a single-sample database, and laying a solid foundation for subsequent face feature extraction and single-sample facial recognition.
B: A method employing generative adversarial network for predicting a face change, comprising: S1 of acquiring face data samples; S2 of constructing a generative adversarial network model consisting of a generator and a discriminator, designing a loss function, and performing iterative training on the generator and the discriminator; and S3 of inputting a target young face image to be processed into the trained generative adversarial network model, and outputting a target aged face image corresponding to the target young face image. The method is adopted to construct a unique generative adversarial network model and loss function, provides robustness for aging, and accounts for change information including the forehead, hair, and the like, thereby improving the accuracy and uniqueness of prediction.
C: Disclosed in the　present invention are an automatic color filling method and apparatus for a building general drawing. Said method comprises: acquiring plane general drawing data of a building, and performing analysis on the basis of preset building basic element features to obtain basic elements of a building general drawing; on the basis of basic element data, generating specific elements according to a preset corresponding policy between the specific elements and the basic elements; receiving and analyzing a color matching mode instruction, and according to corresponding color matching policies of the elements under a preset color matching mode, obtaining color matching schemes of the elements under the selected color matching mode; respectively selecting corresponding colors according to the color matching schemes, so as to perform color matching and filling on the basic elements and the specific elements; and processing, by using a selected picture format conversion policy, the building general drawing of which the color matching and filling has been completed, so as to obtain a color-filled building general drawing in a corresponding picture format. The present invention provides an efficient and highly-accurate solution of automatic color filling for a building general drawing.
D: A prefabricated building wall comprises a main wall (20), a beam (10), a foundation, and a shear wall (30). The beam (10) is mounted at a top end of the main wall (20), and the shear wall (30) is mounted at a bottom end of the main wall (20). The shear wall (30) is filled with a concrete layer (31) and forms the foundation. An outer side surface of the main wall (20) is provided with a bamboo charcoal layer (21). The shear wall (30) comprises a plurality of widthwise support tubes (301), a plurality of lengthwise support tubes (302), and a connecting assembly. The plurality of widthwise support tubes (301) are arranged along a vertical direction of the shear wall (30) and are spaced apart from each other. The plurality of lengthwise support tubes (302) are arranged along a widthwise direction of the shear wall (30) and are spaced apart from each other. A plurality of lengthwise support tubes (302) are connected between two adjacent widthwise support tubes (301). The lengthwise support tubes (302) are fixedly connected to the widthwise support tubes (301) by the connecting assembly. The prefabricated building wall absorbs smoke and dust of an interior space and has a stable shear wall structure.
Answer: C