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 "deeply activated salient region for instance search"):
  Abstract: Due to the lack of suitable feature representation, effective solution to the instance search is still slow to occur. In this paper, a novel instance-level feature descriptor is proposed. The feature is built upon the salient instance region that is activated by a layer-wise back-propagation process. Such kind of region usually covers the major part an instance and represents the common patterns shared among instances of the same category. The back-propagation starts from the last convolution layer of pre-trained CNN that is originally used for classification. This makes the feature representation remain effective for instances from both known and unknown categories. Moreover, experiments show that it is effective for instance as well as image search tasks.

Includes members:
  Member "got 10k a large high diversity benchmark for generic object tracking in the wild":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "siamese box adaptive network for visual tracking")
  Member "c mil continuation multiple instance learning for weakly supervised object detection":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "ehsod cam guided end to end hybrid supervised object detection with cascade refinement")
  Member "weakly supervised instance segmentation using class peak response":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "weakly supervised instance segmentation by deep community learning")
  Member "yolov3 an incremental improvement":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "perception and decision making of autonomous systems in the era of learning an overview")
  Member "instance search via instance level segmentation and feature representation":
    also connected through other hyperedges:
      (none)
  Member "youtube boundingboxes a large high precision human annotated data set for object detection in video":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "siamese attentional keypoint network for high performance visual tracking")
  Member "saliency weighted convolutional features for instance search":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "benchmarking unsupervised near duplicate image detection")
  Member "multiple instance detection network with online instance classifier refinement":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "weakly supervised instance segmentation by deep community learning")

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)