human: Given a node-centered hypergraph: <hypergraph>, where nodes represent authors and hyperedges represent groups of authors who co-authored the same paper.

Details of the hypergraph:
Center node: "DAU-GAN: Unsupervised Object Transfiguration via Deep Attention Unit"
  Abstract: Object transfiguration aims to translate objects in image from a kind to another, which is a subtask of image translation. Recently, researchers have proposed many effective approaches for object transfiguration. However, most of them ignore the difference between target objects and background, which would make background deformation, discolor and other problems. We propose a novel attention-based model for unsupervised object transfiguration called Deep Attention Units Generative Adversarial Network (DAU-GAN). We utilize spatial consistencies of objects and background to enable model to preserve background of image. Such an attention-based design enables DAU-GAN to enhance the expression of meaningful features and let the model able to distinguish specific objects and background in images. Experimental results demonstrate that our approach improves the performance of object transfiguration as well as effectively preserves background.

Connected through hyperedge HE-1 (induced by source paper "Deep Sparse Rectifier Neural Networks"):
  with members:
    - "Opinion Mining and Sentiment Analysis"
    - "DeepNAT: Deep convolutional neural network for segmenting neuroanatomy"
    - "Maxout Networks"
    - "Densely Connected Convolutional Networks"
    - "WiDet: Wi-Fi Based Device-Free Passive Person Detection with Deep Convolutional Neural Networks"

Question: Please tell me which research area the center author belongs to. The 4 classes are: Computer science, Mathematics, Engineering, Economics, Psychology, Business. Directly output the class name.

gpt: Computer science