Skip to main content

Intelligent Creative Design of Textile Patterns Based on Convolutional Neural Network

  • Conference paper
  • First Online:
Advances in Intelligent, Interactive Systems and Applications (IISA 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 885))

Abstract

Deep learning technology has been developing significantly in the field of pattern recognition in recent years. As an important research achievement by theorized principles of human brain function, multi-layer artificial neural network has achieved impressive results in visual processing. In particular, deep dream (DD) is algorithm, based on deep-learning convolutional neural network (CNN), that blends visual qualities from multiple source images to create a new output image and provides a new opportunity for the design of textile patterns. This paper first introduces the CNN model. A model of textile design aided design based on DD is proposed. And based on the depth learning framework Tensorflow and Torch, using the deep neural network GoogleNet and ResNet, realizes the intelligent aided design system of textile pattern based on convolutional neural network.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Keshavan, M.S., Sudarshan, M.: Deep dreaming, aberrant salience and psychosis: connecting the dots by artificial neural networks. Schizophr. Res. 188, 178–181 (2017)

    Article  Google Scholar 

  2. Mordvintsev, A., Olah, C., Tyka, M.: Inceptionism: going deeper into neural networks. googleresearch.blogspot.com/2015/06/inceptionism-going-deeper-intoneural.html

  3. McCaig, G., DiPaola, S., Gabora, L.: Deep convolutional networks as models of generalization and blending within visual creativity. In: Proceedings of the Seventh International Conference on Computational Creativity, pp. 156–163 (2016)

    Google Scholar 

Download references

Acknowledgements

This work was funded by Beijing Science and Technology Program (Z171100005017004).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Wang Ying .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Ying, W., Zhengdong, L. (2019). Intelligent Creative Design of Textile Patterns Based on Convolutional Neural Network. In: Xhafa, F., Patnaik, S., Tavana, M. (eds) Advances in Intelligent, Interactive Systems and Applications. IISA 2018. Advances in Intelligent Systems and Computing, vol 885. Springer, Cham. https://doi.org/10.1007/978-3-030-02804-6_28

Download citation

Publish with us

Policies and ethics