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 "neural architecture based on fuzzy perceptual representation for online multilingual handwriting recognition"):
  Abstract: Due to the omnipresence of mobile devices, online handwritten scripts have become the most important feeding input to smartphones and tablet devices. To increase online handwriting recognition performance, deeper neural networks have extensively been used. In this context, our paper handles the problem of online handwritten script recognition based on extraction features system and deep approach system for sequences classification. Many solutions have appeared in order to facilitate the recognition of handwriting. Accordingly, we used an existent method and combined with new classifiers in order to get a flexible system. Good results are achieved compared to online characters and words recognition system on Latin and Arabic scripts. The performance of our two proposed systems is assessed by using five databases. Indeed, the recognition rate exceeds 98%.

Includes members:
  Member "fast multi language lstm based online handwriting recognition":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the didi dataset digital ink diagram data")
  Member "a gru based encoder decoder approach with attention for online handwritten mathematical expression recognition":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "stroke constrained attention network for online handwritten mathematical expression recognition")
  Member "design of a very compact cnn classifier for online handwritten chinese character recognition using dropweight and global pooling":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fingertip detection and tracking for recognition of air writing in videos")
  Member "drawing and recognizing chinese characters with recurrent neural network":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "deep independently recurrent neural network indrnn")
  Member "improved deep convolutional neural network for online handwritten chinese character recognition using domain specific knowledge":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "pioneer dataset and automatic recognition of urdu handwritten characters using a deep autoencoder and convolutional neural network")
  Member "a hybrid nn hmm modeling technique for online arabic handwriting recognition":
    also connected through other hyperedges:
      (none)

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)