human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge groups authors who co-authored the same paper.

Details of the hypergraph:
Center hyperedge (induced by source paper "Learning Recursive Filters for Low-Level Vision via a Hybrid Neural Network"):
  Abstract: In this paper, we consider numerous low-level vision problems (e.g., edge-preserving filtering and denoising) as recursive image filtering via a hybrid neural network. The network contains several spatially variant recurrent neural networks (RNN) as equivalents of a group of distinct recursive filters for each pixel, and a deep convolutional neural network (CNN) that learns the weights of RNNs. The deep CNN can learn regulations of recurrent propagation for various tasks and effectively guides recurrent propagation over an entire image. The proposed model does not need a large number of convolutional channels nor big kernels to learn features for low-level vision filters. It is significantly smaller and faster in comparison with a deep CNN based image filter. Experimental results show that many low-level vision tasks can be effectively learned and carried out in real-time by the proposed algorithm.

Includes members:
  Member "Deep Convolutional Neural Network for Image Deconvolution":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Image Denoising and Inpainting with Deep Neural Networks")
  Member "Image Denoising and Inpainting with Deep Neural Networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Unsupervised Class-Specific Deblurring")
  Member "Deep bilateral learning for real-time image enhancement":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Embedded deep learning in ophthalmology: Making ophthalmic imaging smarter")

Question: Please tell me which research area the co-authored paper (i.e., the source paper of the center hyperedge) belongs to. The 4 classes are: Computer science, Mathematics, Engineering, Economics, Psychology, Business. Directly output the class name.

gpt: Computer science