human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "exploring new directions in iris recognition"
  Abstract: A new approach in iris recognition based on Circular Fuzzy Iris Segmentation (CFIS) and Gabor Analytic Iris Texture Binary Encoder (GAITBE) is proposed and tested here. CFIS procedure is designed to guarantee that similar iris segments will be obtained for similar eye images, despite the fact that the degree of occlusion may vary from one image to another. Its result is a circular iris ring (concentric with the pupil) which approximates the actual iris. GAITBE proves better encoding of statistical independence between the iris codes extracted from different irides using Hilbert Transform. Irides from University of Bath Iris Database are binary encoded on two different lengths (768 / 192 bytes) and tested in both single-enrollment and multi-enrollment identification scenarios. All cases illustrate the capacity of the newly proposed methodology to narrow down the distribution of inter-class matching scores, and consequently, to guarantee a steeper descent of the False Accept Rate.

Connected through hyperedge HE-1 (induced by source paper "combined haar hilbert and log gabor based iris encoders"):
  with members:
    - "8 valent fuzzy logic for iris recognition and biometry"
    - "iris codes classification using discriminant and witness directions"
    - "exploratory simulation of an intelligent iris verifier distributed system"
    - "from cognitive binary logic to cognitive intelligent agents"
    - "comparing haar hilbert and log gabor based iris encoders on bath iris image database"

Connected through hyperedge HE-2 (induced by source paper "the biometric menagerie a fuzzy and inconsistent concept"):
  with members:
    - "combined haar hilbert and log gabor based iris encoders"
    - "8 valent fuzzy logic for iris recognition and biometry"
    - "iris codes classification using discriminant and witness directions"
    - "comparing haar hilbert and log gabor based iris encoders on bath iris image database"

Connected through hyperedge HE-3 (induced by source paper "noise influence on the fuzzy linguistic partitioning of iris code space"):
  with members:
    - "combined haar hilbert and log gabor based iris encoders"
    - "8 valent fuzzy logic for iris recognition and biometry"
    - "iris codes classification using discriminant and witness directions"
    - "comparing haar hilbert and log gabor based iris encoders on bath iris image database"

Connected through hyperedge HE-4 (induced by source paper "from cognitive binary logic to cognitive intelligent agents"):
  with members:
    - "cognitive binary logic the natural unified formal theory of propositional binary logic"

Connected through hyperedge HE-5 (induced by source paper "comparing haar hilbert and log gabor based iris encoders on bath iris image database"):
  with members:
    - "a fuzzy view on k means based signal quantization with application in iris segmentation"

Question: Please tell me which class the center node 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)