Search Results for author: Peter Childs

Found 5 papers, 1 papers with code

WikiLink: an encyclopedia-based semantic network for design innovation

1 code implementation30 Aug 2022 Haoyu Zuo, Qianzhi Jing, Tianqi Song, Huiting Liu, Lingyun Sun, Peter Childs, Liuqing Chen

However, existing semantic networks for design innovation is built on data source restricted to technological and scientific information.

Patent-KG: Patent Knowledge Graph Use for Engineering Design

no code implementations26 Aug 2021 Haoyu Zuo, Yuan Yin, Peter Childs

This paper builds a patent-based knowledge graph, patent-KG, to represent the knowledge facts in patents for engineering design.

Negation

Product semantics translation from brain activity via adversarial learning

no code implementations29 Mar 2021 Pan Wang, Zhifeng Gong, Shuo Wang, Hao Dong, Jialu Fan, Ling Li, Peter Childs, Yike Guo

To modify a design semantic of a given product from personalised brain activity via adversarial learning, in this work, we propose a deep generative transformation model to modify product semantics from the brain signal.

EEG Electroencephalogram (EEG) +1

Verifying Design through Generative Visualization of Neural Activities

no code implementations28 Mar 2021 Pan Wang, Danlin Peng, Simiao Yu, Chao Wu, Peter Childs, Yike Guo, Ling Li

A recurrent neural network is used as the encoder to learn latent representation from electroencephalogram (EEG) signals, recorded while subjects looked at 50 categories of images.

EEG Electroencephalogram (EEG) +1

A General Framework for Revealing Human Mind with auto-encoding GANs

no code implementations10 Feb 2021 Pan Wang, Rui Zhou, Shuo Wang, Ling Li, Wenjia Bai, Jialu Fan, Chunlin Li, Peter Childs, Yike Guo

For this reason, we propose an end-to-end brain decoding framework which translates brain activity into an image by latent space alignment.

Brain Decoding

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