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: "tooth morphometry using quasi conformal theory"
  Abstract: Abstract   Shape analysis is important in anthropology, bioarchaeology and forensic science for interpreting useful information from human remains. In particular, teeth are morphologically stable and hence well-suited for shape analysis. In this work, we propose a framework for tooth morphometry using quasi-conformal theory. Landmark-matching Teichmuller maps are used for establishing a 1-1 correspondence between tooth surfaces with prescribed anatomical landmarks. Then, a quasi-conformal statistical shape analysis model based on the Teichmuller mapping results is proposed for building a tooth classification scheme. We deploy our framework on a dataset of human premolars to analyze the tooth shape variation among genders and ancestries. Experimental results show that our method achieves much higher classification accuracy with respect to both gender and ancestry when compared to the existing methods. Furthermore, our model reveals the underlying tooth shape difference between different genders and ancestries in terms of the local geometric distortion and curvatures. In particular, our experiment suggests that the shape difference between genders is mostly captured by the conformal distortion but not the curvatures, while that between ancestries is captured by both of them.

Connected through hyperedge HE-1 (induced by source paper "shape analysis via inconsistent surface registration"):
  with members:
    - "inconsistent surface registration via optimization of mapping distortions"
    - "parallelizable global conformal parameterization of simply connected surfaces via partial welding"
    - "boundary first flattening"
    - "density equalizing maps for simply connected open surfaces"
    - "a novel stretch energy minimization algorithm for equiareal parameterizations"
    - "fast spherical quasiconformal parameterization of genus 0 closed surfaces with application to adaptive remeshing"
    - "tempo feature endowed teichm uller extremal mappings of point clouds"
    - "a linear formulation for disk conformal parameterization of simply connected open surfaces"

Connected through hyperedge HE-2 (induced by source paper "parallelizable global conformal parameterization of simply connected surfaces via partial welding"):
  with members:
    - "area preserving mapping of 3d ultrasound carotid artery images using density equalizing reference map"
    - "boundary first flattening"
    - "density equalizing maps for simply connected open surfaces"
    - "a novel stretch energy minimization algorithm for equiareal parameterizations"
    - "fast spherical quasiconformal parameterization of genus 0 closed surfaces with application to adaptive remeshing"
    - "tempo feature endowed teichm uller extremal mappings of point clouds"
    - "sparsified cholesky and multigrid solvers for connection laplacians"
    - "a linear formulation for disk conformal parameterization of simply connected open surfaces"

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)