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 "text extraction from texture images using masked signal decomposition"):
  Abstract: Text extraction is an important problem in image processing with applications from optical character recognition to autonomous driving. Most of the traditional text segmentation algorithms consider separating text from a simple background (which usually has a different color from texts). In this work we consider separating texts from a textured background, that has similar color to texts. We look at this problem from a signal decomposition perspective, and consider a more realistic scenario where signal components are overlaid on top of each other (instead of adding together). When the signals are overlaid, to separate signal components, we need to find a binary mask which shows the support of each component. Because directly solving the binary mask is intractable, we relax this problem to the approximated continuous problem, and solve it by alternating optimization method. We show that the proposed algorithm achieves significantly better results than other recent works on several challenging images.

Includes members:
  Member "masked signal decomposition using subspace representation and its applications":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "compressed sensing with probability based prior information")
  Member "screen content image segmentation using robust regression and sparse decomposition":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "finger gan generating realistic fingerprint images using connectivity imposed gan")
  Member "text flow a unified text detection system in natural scene images":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "exploring the capacity of sequential free box discretization network for omnidirectional scene text detection")
  Member "textproposals a text specific selective search algorithm for word spotting in the wild":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "integrating scene text and visual appearance for fine grained image classification")
  Member "screen content image segmentation using sparse decomposition and total variation minimization":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "subspace learning in the presence of sparse structured outliers and noise")
  Member "iris recognition using scattering transform and textural features":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "deepiris iris recognition using a deep learning approach")
  Member "fingerprint recognition using translation invariant scattering network":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a study on wrist identification for forensic investigation")
  Member "a hough transform based technique for text segmentation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a review on automatic license plate recognition system")

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)