Imperial College London
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ProfessorPeterChilds

Faculty of Engineering

Co-Director of the Energy Futures Lab (EFL)
 
 
 
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Contact

 

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Location

 

Studio 1, Dyson BuildingDyson BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Wang:2019:10.1017/dsi.2019.264,
author = {Wang, P and Peng, D and Li, L and Chen, L and Wu, C and Wang, X and Childs, P and Guo, Y},
doi = {10.1017/dsi.2019.264},
pages = {2577--2586},
publisher = {Cambridge University Press (CUP)},
title = {Human-in-the-loop design with machine learning},
url = {http://dx.doi.org/10.1017/dsi.2019.264},
year = {2019}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - Deep learning methods have been applied to randomly generate images, such as in fashion, furniture design. To date, consideration of human aspects which play a vital role in a design process has not been given significant attention in deep learning approaches. In this paper, results are reported from a human- in-the-loop design method where brain EEG signals are used to capture preferable design features. In the framework developed, an encoder extracting EEG features from raw signals recorded from subjects when viewing images from ImageNet are learned. Secondly, a GAN model is trained conditioned on the encoded EEG features to generate design images. Thirdly, the trained model is used to generate design images from a person's EEG measured brain activity in the cognitive process of thinking about a design. To verify the proposed method, a case study is presented following the proposed approach. The results indicate that the method can generate preferred designs styles guided by the preference related brain signals. In addition, this method could also help improve communication between designers and clients where clients might not be able to express design requests clearly.
AU  - Wang,P
AU  - Peng,D
AU  - Li,L
AU  - Chen,L
AU  - Wu,C
AU  - Wang,X
AU  - Childs,P
AU  - Guo,Y
DO  - 10.1017/dsi.2019.264
EP  - 2586
PB  - Cambridge University Press (CUP)
PY  - 2019///
SP  - 2577
TI  - Human-in-the-loop design with machine learning
UR  - http://dx.doi.org/10.1017/dsi.2019.264
UR  - https://www.cambridge.org/core/journals/proceedings-of-the-international-conference-on-engineering-design/article/humanintheloop-design-with-machine-learning/3A5B1A14E4F0701B3376F3C3AEB89D86
UR  - http://hdl.handle.net/10044/1/77409
ER  -
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