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 "iris recognition in cases of eye pathology"):
  Abstract: The purpose of this chapter is to provide an insight on iris recognition system performances for users suffering from some ocular pathologies. Such situations are analyzed in terms of influences and possible means are discussed to take this case into account during the phase of iris samples matching.

Includes members:
  Member "implications of ocular pathologies for iris recognition reliability":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "iris recognition after death")
  Member "human iris recognition in post mortem subjects study and database":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "sip segnet a deep convolutional encoder decoder network for joint semantic segmentation and extraction of sclera iris and pupil based on periocular region suppression")
  Member "post mortem human iris recognition":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "sip segnet a deep convolutional encoder decoder network for joint semantic segmentation and extraction of sclera iris and pupil based on periocular region suppression")
  Member "database of iris images acquired in the presence of ocular pathologies and assessment of iris recognition reliability for disease affected eyes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "post mortem iris recognition with deep learning based image segmentation")
  Member "assessment of iris recognition reliability for eyes affected by ocular pathologies":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "implications of ocular pathologies for iris recognition reliability")
  Member "linear regression analysis of template aging in iris biometrics":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "implications of ocular pathologies for iris recognition reliability")
  Member "cataract influence on iris recognition performance":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "implications of ocular pathologies for iris recognition reliability")

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)