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: "a fractal based cnn for detecting complicated curves in afm images"
  Abstract: Convolutional neural networks (CNNs) have been widely used in computer vision, including low-and middle-level vision problems such as contour detection and image reconstruction. In this paper, we propose a novel fractal-based CNN model for the problem of complicated curve detection, providing a geometric interpretation of CNN-based image model leveraging local fractal analysis. Utilizing the notion of local self-similarity, we develop a local fractal model for images. A curve detector is designed based on the model, consisting of an orientation-adaptive filtering process to enhance the local response along a certain orientation. This is followed by a post-processing step to preserve local invariance of the fractal dimension of image. We show the iterative framework of such an adaptive filtering process can be re-instantiated approximately via a CNN model, the nonlinear processing layer of which preserves fractal dimension approximately and the convolution layer achieves orientation enhancement. We demonstrate our fractal-based CNN model on the challenging task for detecting complicated curves from the texture-like images depicting microstructures of materials obtained by atomic force microscopy (AFM).

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)