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 "arbitrary oriented scene text detection via rotation proposals"):
  Abstract: This paper introduces a novel rotation-based framework for arbitrary-oriented text detection in natural scene images. We present the  Rotation Region Proposal Networks , which are designed to generate inclined proposals with text orientation angle information. The angle information is then adapted for bounding box regression to make the proposals more accurately fit into the text region in terms of the orientation. The  Rotation Region-of-Interest  pooling layer is proposed to project arbitrary-oriented proposals to a feature map for a text region classifier. The whole framework is built upon a region-proposal-based architecture, which ensures the computational efficiency of the arbitrary-oriented text detection compared with previous text detection systems. We conduct experiments using the rotation-based framework on three real-world scene text detection datasets and demonstrate its superiority in terms of effectiveness and efficiency over previous approaches.

Includes members:
  Member "deep matching prior network toward tighter multi oriented text detection":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "relatext exploiting visual relationships for arbitrary shaped scene text detection with graph convolutional networks")
  Member "improving text proposals for scene images with fully convolutional networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "selective style transfer for text")
  Member "cascaded segmentation detection networks for word level text spotting":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "automatic semantic content removal by learning to neglect")
  Member "integrating scene text and visual appearance for fine grained image classification":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "fine grained image classification and retrieval by combining visual and locally pooled textual features")
  Member "detecting oriented text in natural images by linking segments":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "relatext exploiting visual relationships for arbitrary shaped scene text detection with graph convolutional networks")
  Member "evolving boxes for fast vehicle detection":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "spotnet self attention multi task network for object detection")
  Member "text flow a unified text detection system in natural scene images":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "exploring the capacity of sequential free box discretization network for omnidirectional scene text detection")
  Member "character proposal network for robust text extraction":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "selective distillation of weakly annotated gtd for vision based slab identification 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)