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 "privacy preserving action recognition for smart hospitals using low resolution depth images"):
  Abstract: Computer-vision hospital systems can greatly assist healthcare workers and improve medical facility treatment, but often face patient resistance due to the perceived intrusiveness and violation of privacy associated with visual surveillance. We downsample video frames to extremely low resolutions to degrade private information from surveillance videos. We measure the amount of activity-recognition information retained in low resolution depth images, and also apply a privately-trained DCSCN super-resolution model to enhance the utility of our images. We implement our techniques with two actual healthcare-surveillance scenarios, hand-hygiene compliance and ICU activity-logging, and show that our privacy-preserving techniques preserve enough information for realistic healthcare tasks.

Includes members:
  Member "fast and accurate single image super resolution via information distillation network":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "learning enriched features for real image restoration and enhancement")
  Member "fully coupled two stream spatiotemporal networks for extremely low resolution action recognition":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "extreme low resolution activity recognition with spatial temporal attention transfer")
  Member "low resolution face recognition in the wild":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "low resolution face recognition in the wild via selective knowledge distillation")
  Member "towards vision based smart hospitals a system for tracking and monitoring hand hygiene compliance":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "convolutional relational machine for group activity recognition")
  Member "extreme low resolution activity recognition with multi siamese embedding learning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "are accelerometers for activity recognition a dead end")
  Member "a review of privacy and consent management in healthcare a focus on emerging data sources":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "characterizing iot data and its quality for use")
  Member "fast and accurate image super resolution by deep cnn with skip connection and network in network":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "learned multi view texture super resolution")
  Member "low resolution face recognition using a two branch deep convolutional neural network architecture":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "relational deep feature learning for heterogeneous face recognition")

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)