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 "deep autoencoders with value at risk thresholding for unsupervised anomaly detection"):
  Abstract: Many real-world monitoring and surveillance applications require non-trivial anomaly detection to be run in the streaming model. We consider an incremental-learning approach, wherein a deep-autoencoding (DAE) model of what is normal is trained and used to detect anomalies at the same time. In the detection of anomalies, we utilise a novel thresholding mechanism, based on value at risk (VaR). We compare the resulting convolutional neural network (CNN) against a number of subspace methods, and present results on changedetection net.

Includes members:
  Member "background subtraction in real applications challenges current models and future directions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "moving objects detection with a moving camera a comprehensive review")
  Member "learning multi scale features for foreground segmentation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "moving objects detection with a moving camera a comprehensive review")
  Member "deep neural network concepts for background subtraction a systematic review and comparative evaluation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "moving objects detection with a moving camera a comprehensive review")
  Member "an overview of robust subspace recovery":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "finding the sparsest vectors in a subspace theory algorithms and applications")
  Member "robust subspace learning robust pca robust subspace tracking and robust subspace recovery":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "moving objects detection with a moving camera a comprehensive review")
  Member "a deep convolutional neural network for background subtraction":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "moving objects detection with a moving camera a comprehensive review")
  Member "robust online matrix factorization for dynamic background subtraction":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a robust visual system for small target motion detection against cluttered moving backgrounds")
  Member "fast optical flow using dense inverse search":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "learning the sense of touch in simulation a sim to real strategy for vision based tactile sensing")

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)