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 "separation surfaces in the spectral tv domain for texture decomposition"):
  Abstract: In this paper, we introduce a novel notion of separation surfaces for image decomposition. A surface is embedded in the spectral total-variation (TV) 3D domain and encodes a spatially varying separation scale. The method allows good separation of textures with gradually varying pattern size, pattern contrast, or illumination. The recently proposed TV spectral framework is used to decompose the image into a continuum of textural scales. A desired texture, within a scale range, is found by fitting a surface to the local maximal responses in the spectral domain. A band above and below the surface, referred to as the texture stratum, defines for each pixel the adaptive scale range of the texture. Based on the decomposition, an application is proposed, which can attenuate or enhance textures in the image in a very natural and visually convincing manner.

Includes members:
  Member "spectral decompositions using one homogeneous functionals":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "flows generating nonlinear eigenfunctions")
  Member "adaptive diffusion constrained total variation scheme with application to cartoon texture edge image decomposition":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "robust periocular recognition by fusing sparse representations of color and geometry information")
  Member "robust recovery of subspace structures by low rank representation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "gated fusion network for degraded image super resolution")

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)