Application of Convolutional Neural Network Algorithm under Deep Learning in Digital Clothing Design

Abstract

In order to overcome the influence of background, lighting, deformation, and other factors, using a constitutional neural network structure combined with metric learning, specifically, it includes two model structures, Siamese, and Triplet. The use of bicubic NURBS surfaces is proposed, the idea of constructing mannequins and garment pieces, the experimental results show that NURBS surface control is flexible and simple, and the calculation is stable, and it is the best surface for constructing virtual samples and avatars. Based on studying the three-dimensional structure design of clothing, based on the 10 key curves of the human body, the curve and surface interpolation algorithm is applied, by calling OpenGL related functions, the establishment of the benchmark human body model is well realized, and it lays a foundation for the deformation of the human body model based on parameters in the future.

Thin Shell Model of a Coated Conductor with a Ferromagnetic Substrate

“…8). A Matlab code for calculating the analytical solution [1] was in this case kindly provided by Dr Cun Xue [30]. As in the Meissner case, our solution is close to that in [23] for small  and to the solution in [1] dashed curve) the losses should be close to those for a nonmagnetic substrate.…”

Research on Culinary Fruits and Vegetables and Fresh-Cut Vegetables Recognition Based on Convolutional Neural Network

“…It generally uses downsampling to obtain half of the matrix data while maintaining spatial features such as translation invariance, rotation invariance and relative scale invariance. Pooling methods include general pooling, overlap pooling and pyramid pooling [17], where general pooling contains average pooling and maximum pooling. Average pooling calculates the average value of the numbers in the image region as the pooled value, while maximum pooling selects the maximum value in the region as the pooled value.…”

Application of Clothing Design Based on Computer Vision Technology Using Hybrid Graph Convolution Neural Network and Lotus Effect Optimization Algorithm

“…The silhouette curve, reference point, and feature size were all calculated using a model that was created to calculate the form ratio and silhouette form value for style identification were used to characterize the garment silhouette information [8,9]. Unfortunately, the previously suggested techniques perform poorly when it comes to identifying clothing styles with strong silhouette variances and strong similarities [10,11]. Classification is a possible formulation for the definition problem of the picture of clothing.…”