Tacit magic: understanding the principles behind Nakamichi’s creative pattern cutting

McKinney, Ellen; Stanley, April Elisha; Plummer, Brianna; Thompson, Kate; Rorah, Whitney

doi:10.1080/17543266.2016.1165740

Cited by 4 publications

(3 citation statements)

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“…The convolution layer of CNN is the core of the whole network and has features of weight sharing and local area perception. Its input source comes from the sampling layer and the input layer, respectively, and the output is the input of the sampling layer [6]. The convolution operation can denoise and enhance the source signal and is also regarded as a correlation operation within the scope of linear operations.…”

Section: Methodsmentioning

confidence: 99%

Application of convolution neural networks‐based hierarchical perception technology in 3D clothing designs

Hong

2022

IET Networks

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The purpose of this research is to solve the problems in the modern life, such as the inconvenience caused by fast life pace, the need to save time, the unsatisfactory products for consumers, the low brand awareness in the clothing industry, serious product homogenisation and low life quality. The study of the application of hierarchical perception technology in 3D (three‐dimensional) clothing designs is carried out based on CNN (convolutional neural networks). The study includes the training of CNN, the selection of 3D clothing models and 2D (two‐dimensional) projection of 3D human body models. A simulation experiment is conducted by taking 49‐year‐old males, 22‐year‐old males and 50‐year‐old females as research objects. The findings show that the training network can effectively identify the typical lines of the human's hindneck, chest, shoulders, and waist, and the accuracy of the front and side recognition of the human body can be reached as high as 93% on average. The effective identification of human characteristics is achieved. The study has an important impact on the technical field and clothing industry and also has profound theoretical and practical significance.

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Section: Methodsmentioning

confidence: 99%

Application of convolution neural networks‐based hierarchical perception technology in 3D clothing designs

Hong

2022

IET Networks

View full text Add to dashboard Cite

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“…The focus of the course was on the research, analysis, and application of experimental patternmaking techniques to original garments. The course began with a discussion of theory in patternmaking (Pedersen 2007;Lindqvist 2015;McKinney et al 2016;Bye 2010) and a review of the traditional patternmaking principles: dart manipulation, added fullness, and contouring (Joseph-Armstrong 2010). The course investigated several types of sustainability related patternmaking.…”

Section: Sample and Data Collectionmentioning

confidence: 99%

“…Each student was required to complete a PMTSA on a zero waste patternmaking method of her choice. PMTSA is a standardized process for testing and analyzing patternmaking approaches (McKinney et al 2016). The steps are as follows.…”

Section: Sample and Data Collectionmentioning

confidence: 99%