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 "online visual robot tracking and identification using deep lstm networks"):
  Abstract: Collaborative robots working on a common task are necessary for many applications. One of the challenges for achieving collaboration in a team of robots is mutual tracking and identification. We present a novel pipeline for online visionbased detection, tracking and identification of robots with a known and identical appearance. Our method runs in realtime on the limited hardware of the observer robot. Unlike previous works addressing robot tracking and identification, we use a data-driven approach based on recurrent neural networks to learn relations between sequential inputs and outputs. We formulate the data association problem as multiple classification problems. A deep LSTM network was trained on a simulated dataset and fine-tuned on small set of real data. Experiments on two challenging datasets, one synthetic and one real, which include long-term occlusions, show promising results.

Includes members:
  Member "a monocular vision system for playing soccer in low color information environments":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "utilizing temporal information in deep convolutional network for efficient soccer ball detection and tracking")
  Member "real time visual tracking and identification for a team of homogeneous humanoid robots":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "robocup 2019 adultsize winner nimbro deep learning perception in walk kick push recovery and team play capabilities")
  Member "child sized 3d printed igus humanoid open platform":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "nimbro op2x adult sized open source 3d printed humanoid robot")
  Member "lstm a search space odyssey":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "refined gate a simple and effective gating mechanism for recurrent units")
  Member "robust and real time deep tracking via multi scale domain adaptation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "rethinking convolutional features in correlation filter based tracking")
  Member "tracking the untrackable learning to track multiple cues with long term dependencies":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "multiple object tracking by flowing and fusing")
  Member "globally consistent multi people tracking using motion patterns":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "trajectory factory tracklet cleaving and re connection by deep siamese bi gru for multiple object tracking")
  Member "end to end tracking and semantic segmentation using recurrent neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "graph neural based end to end data association framework for online multiple object tracking")

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.RO(Robotics)