2D Pattern Design of Upper Outer from 3D Specification Based on Neural Networks

2006 ◽  
pp. 805-814
Author(s):  
Dongyun Wang ◽  
Yulin Xu
Keyword(s):  
Neural Networks ◽  
Pattern Design ◽  
2D Pattern

The knitting methods for seamless garments based on four-needle bed computerized flat machine

2021 ◽  
pp. 004051752110351
Author(s):  
Lisha Lu ◽  
Gaoming Jiang ◽  
Guangjun Wu
Keyword(s):  
Design Process ◽  
Production Efficiency ◽  
Design System ◽  
Great Contribution ◽  
Pattern Design ◽  
Traditional Technology ◽  
Different Types ◽  
2D Pattern ◽  
Seamless Knitting ◽  
Transformation Methods

Seamless garments reducing the cutting and sewing processes are created using seamless knitting technology. This type of garment, being less dependent on labor, is knitted as a whole and makes a great contribution to improving production efficiency. More importantly, seamless garments are more comfortable and natural compared with those styles produced by traditional technology. However, the techniques of seamless garments are huge and complex, making the pattern design process more difficult. In addition, the seamless knitting technology has great restrictions to the styles with rich shapes due to the limitation of the devices. Therefore, how to knit more complex styles using seamless knitting technology still faces great challenges. For these reasons, this study extensively investigated the knitting principle of seamless garments and proposed six knitting models for different kinds of garments. Then the transformation methods from 3D style to 2D pattern were explored respectively based on the knitting characteristics of each model. Finally, by package programming in the SDS-ONE APEX design system, the actual knitting for six types of garments was conducted on the computerized flat knitting machine. The results showed that different types of seamless garments have significant differences in the pattern design and the approaches proposed above can make different kinds of garments using seamless knitting technology.

P‐143: TSP Pattern Design and Sensitivity Characterization via Convolutional Neural Networks

2019 ◽  
Vol 50 (1) ◽  
pp. 1763-1766
Author(s):  
Hyun Sung Park ◽  
Choong Min Jeong ◽  
Keuk Jin Jeong ◽  
Suyul Seo ◽  
Yujin Choi ◽  
...  
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Pattern Design

scholarly journals Punch Card Patterns Designed with GAN

2021 ◽  
pp. 69-79
Author(s):  
Virginia Ellyn Melnyk
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Image Database ◽  
Generative Adversarial Networks ◽  
Punch Card ◽  
Pattern Design ◽  
Style Transfer ◽  
Adversarial Networks ◽  
Design Techniques

AbstractKnitting punch cards codify different stitch patterns into binary patterns, telling the machine when to change color or to generate different stitch types. This research utilizes Neural Networks (NN) and image-based Generative Adversarial Networks (GAN), with an image database of knitting punch cards, to generate new punch card designs. The hypothesis is that artificial intelligence will learn the basic underlying structures of the punch cards and the pattern makeup that is inherent across patterns of different styles and cultures. Different neural networks were utilized throughout the research, such as Neural Style Transfer (NST), AdaIN Style Transfers, and StyleGAN2. The results from these explorations offer different insights into pattern design and various outcomes of the different neural networks. Ultimately physically testing these punch card designs, these patterns were knit on a domestic knitting machine, resulting in novel fabrication and design techniques that are both digital and craft-based.

scholarly journals Development of shirt pattern for wheelchair tennis players through 3D avatars

2020 ◽  
Vol 6 (2) ◽  
Author(s):  
Hee Jae Jin ◽  
Kathy Mullet
Keyword(s):  
Morphological Analysis ◽  
Back Surface ◽  
Surface Zone ◽  
Body Movements ◽  
Pattern Design ◽  
Tennis Players ◽  
2D Pattern ◽  
Block Pattern ◽  
Body Scanner ◽  
Shoulder Blade

This study is to develop the wheelchair tennis pattern to improve comfort by reducing garment strain in a CAD program by analyzing seven body movements related to garment strain during play. The bodice was subdivided into surface zones in the present study to efficiently develop 2D patterns that can later be transferred into 3D virtual garments and draped onto 3D avatars. The 2D patterns were developed based on morphological analysis that provided different possible solutions to enhance comfort by releasing garment strain at each surface zone. The structural lines and wearing ease grade points were utilized to adjust a tennis shirt block pattern when developing this 2D pattern at morphological analysis step. In this study, 3D body scanner was used to create 3D avatars with postures based on the determined seven body movements. The drafted pattern was used to drape the virtual garments on the each movement of 3D avatars in the CAD program, and then the stain areas of the pattern design were identified using the tension map. In all of the movements, the majority of garment strain appeared on the shoulder surface and around the neck within the surface zone of bodice shoulder angle. The majority of other strain found was on the shoulder blade as the bodice bust zone during movements in the forehand swing, backhand swing, serve toss, and serve follow through postures. Based on these strain results obtained from 3D scanner, the first pattern was developed to release strains in shoulder as seen by the significant decrease in strain during both forehand movements. The second pattern was constructed to release other maximized strain on the back surface zone of the shoulder blade. Based on the results of this study, it should be noted that the shoulder and the shoulder blade areas are important during development of patterns in terms of decreasing strain for comfort during wheelchair tennis play movements.

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