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 "a personalized affective memory neural model for improving emotion recognition"):
  Abstract: Recent models of emotion recognition strongly rely on supervised deep learning solutions for the distinction of general emotion expressions. However, they are not reliable when recognizing online and personalized facial expressions, e.g., for person-specific affective understanding. In this paper, we present a neural model based on a conditional adversarial autoencoder to learn how to represent and edit general emotion expressions. We then propose Grow-When-Required networks as personalized affective memories to learn individualized aspects of emotion expressions. Our model achieves state-of-the-art performance on emotion recognition when evaluated on \textit{in-the-wild} datasets. Furthermore, our experiments include ablation studies and neural visualizations in order to explain the behavior of our model.

Includes members:
  Member "affectnet a database for facial expression valence and arousal computing in the wild":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "cascade ef gan progressive facial expression editing with local focuses")
  Member "training deep neural networks with different datasets in the wild the emotion recognition paradigm":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "emotion generation and recognition a stargan approach")
  Member "the omg emotion behavior dataset":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multitask emotion recognition with incomplete labels")
  Member "lifelong learning of spatiotemporal representations with dual memory recurrent self organization":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "human action recognition and assessment via deep neural network self organization")
  Member "unsupervised deep representations for learning audience facial behaviors":
    also connected through other hyperedges:
      (none)
  Member "a deep network for arousal valence emotion prediction with acoustic visual cues":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "exploiting multi cnn features in cnn rnn based dimensional emotion recognition on the omg in the wild dataset")
  Member "multimodal emotion recognition for one minute gradual emotion challenge":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "exploiting multi cnn features in cnn rnn based dimensional emotion recognition on the omg in the wild dataset")
  Member "emotiw 2018 audio video student engagement and group level affect prediction":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "region attention networks for pose and occlusion robust facial expression 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)