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: "image differential invariants"
  Abstract: Inspired by the methods of systematic derivation of image moment invariants, we design two fundamental differential operators to generate image differential invariants for the action of 2D Euclidean, similarity and affine transformation groups. Each differential invariant obtained by using the new method can be expressed as a homogeneous polynomial of image partial derivatives. When setting the degree of the polynomial and the order of image partial derivatives are less than or equal to 4, we generate all Euclidean differential invariants and discuss the independence of them in detail. In the experimental part, we find the relation between Euclidean differential invariants and Gaussian-Hermite moment invariants when using the derivatives of Gaussian to estimate image partial derivatives. Texture classification and image patch verification are carried out on some synthetic and popular real databases. We mainly evaluate the stability and discriminability of Euclidean differential invariants and analyse the effects of various factors on performance of them. The experimental results validate image Euclidean differential invariants have better performance than some commonly used local image features in most cases.

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)