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 "fmhash deep hashing of in air handwriting for user identification"):
  Abstract: Gesture biometrics are gaining popularity with gesture input interface on mobile and Virtual Reality (VR) platforms that lack a keyboard or touchscreen to type a password for user authentication. However, less attention is paid to the gesture-based user identification problem, which essentially requires indexing and searching the gesture motion templates in a large database efficiently. In this paper, we propose FMHash, a user identification framework that can generate a compact binary hash code from a piece of in-air-handwriting of an ID string, which allows fast search in a database of in-air-handwriting templates through a hash table. To demonstrate the effectiveness of the framework, we implemented a prototype and report preliminary results (~98% precision and ~93% recall). More detailed evaluation, comparison, and improvement is working-in-progress. The ability of hashing in-air-handwriting pattern to binary code can be used to achieve convenient sign-in and sign-up with in-air-handwriting gesture ID on future mobile and VR devices.

Includes members:
  Member "deep saliency hashing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "simultaneous region localization and hash coding for fine grained image retrieval")
  Member "tensorflow a system for large scale machine learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")
  Member "deep semantic ranking based hashing for multi label image retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a survey on deep hashing methods")
  Member "simultaneous feature learning and hash coding with deep neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a survey on deep hashing methods")
  Member "bit scalable deep hashing with regularized similarity learning for image retrieval and person re identification":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a survey on deep hashing methods")
  Member "adam a method for stochastic optimization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")
  Member "very deep convolutional networks for large scale image recognition":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "discrimination aware network pruning for deep model compression")

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)