human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "face recognition using scattering convolutional network"):
  Abstract: Face recognition has been an active research area in the past few decades. In general, face recognition can be very challenging due to variations in viewpoint, illumination, facial expression, etc. Therefore it is essential to extract features which are invariant to some or all of these variations. Here a new image representation, called scattering transform/network, has been used to extract features from faces. The scattering transform is a kind of convolutional network which provides a powerful multi-layer representation for signals. After extraction of scattering features, PCA is applied to reduce the dimensionality of the data and then a multi-class support vector machine is used to perform recognition. The proposed algorithm has been tested on three face datasets and achieved a very high recognition rate.

Includes members:
  Member "masked signal decomposition using subspace representation and its applications":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "compressed sensing with probability based prior information")
  Member "person re identification using visual attention":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "context aware road user importance estimation icare")
  Member "screen content image segmentation using robust regression and sparse decomposition":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "finger gan generating realistic fingerprint images using connectivity imposed gan")
  Member "palmprint recognition using deep scattering convolutional network":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "towards unconstrained palmprint recognition on consumer devices a literature review")
  Member "medical image classification via svm using lbp features from saliency based folded data":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "subtractive perceptrons for learning images a preliminary report")
  Member "iris recognition using scattering transform and textural features":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "deepiris iris recognition using a deep learning approach")
  Member "fingerprint recognition using translation invariant scattering network":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a study on wrist identification for forensic investigation")
  Member "a bayesian framework for sparse representation based 3 d human pose estimation":
    also connected through other hyperedges:
      (none)

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.CV(Computer Vision and Pattern Recognition)