human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "generalized optimal sub pattern assignment metric"
  Abstract: This paper presents the generalized optimal sub-pattern assignment (GOSPA) metric on the space of finite sets of targets. Compared to the well-established optimal sub-pattern assignment (OSPA) metric, GOSPA is not normalised by the cardinality of the largest set and it penalizes cardinality errors differently, which enables us to express it as an optimisation over assignments instead of permutations. An important consequence of this is that GOSPA allows us to penalize localization errors for detected targets and the errors due to missed and false targets, as indicated by traditional multiple target tracking (MTT) performance measures, in a sound manner. In addition, we extend the GOSPA metric to the space of random finite sets, which is important to evaluate MTT algorithms via simulations in a rigorous way.

Connected through hyperedge HE-1 (induced by source paper "decentralized poisson multi bernoulli filtering for vehicle tracking"):
  with members:
    - "poisson multi bernoulli mixture filter direct derivation and implementation"
    - "mono camera 3d multi object tracking using deep learning detections and pmbm filtering"
    - "robust distributed fusion with labeled random finite sets"
    - "multisensor poisson multi bernoulli filter for joint target sensor state tracking"
    - "distributed fusion with multi bernoulli filter based on generalized covariance intersection"
    - "extended object tracking introduction overview and applications"
    - "a metric on the space of finite sets of trajectories for evaluation of multi target tracking algorithms"
    - "marginal multi bernoulli filters rfs derivation of mht jipda and association based member"

Connected through hyperedge HE-2 (induced by source paper "a belief propagation algorithm for multipath based slam"):
  with members:
    - "a scalable algorithm for tracking an unknown number of targets using multiple sensors"
    - "cooperative simultaneous localization and synchronization in mobile agent networks"
    - "variational bayesian inference of line spectra"
    - "marginal multi bernoulli filters rfs derivation of mht jipda and association based member"
    - "approximate evaluation of marginal association probabilities with belief propagation"
    - "evaluation of position related information in multipath components for indoor positioning"

Connected through hyperedge HE-3 (induced by source paper "trajectory phd and cphd filters"):
  with members:
    - "multiple target tracking based on sets of trajectories"
    - "a metric on the space of finite sets of trajectories for evaluation of multi target tracking algorithms"
    - "an efficient variational approximation of the best fitting multi bernoulli filter"

Connected through hyperedge HE-4 (induced by source paper "localization recall precision lrp a new performance metric for object detection"):
  with members:
    - "good features to correlate for visual tracking"
    - "t cnn tubelets with convolutional neural networks for object detection from videos"
    - "towards high performance video object detection"
    - "focal loss for dense object detection"
    - "detect to track and track to detect"
    - "ssd single shot multibox detector"
    - "context matters refining object detection in video with recurrent neural networks"
    - "r fcn object detection via region based fully convolutional networks"

Connected through hyperedge HE-5 (induced by source paper "measurement wise occlusion in multi object tracking"):
  with members:
    - "poisson multi bernoulli mixture filter direct derivation and implementation"
    - "fully convolutional neural networks for dynamic object detection in grid maps"
    - "mot16 a benchmark for multi object tracking"
    - "a random finite set approach for dynamic occupancy grid maps with real time application"
    - "approximate evaluation of marginal association probabilities with belief propagation"
    - "hybrid poisson and multi bernoulli filters"

Connected through hyperedge HE-6 (induced by source paper "poisson multi bernoulli mixture filter direct derivation and implementation"):
  with members:
    - "a scalable algorithm for tracking an unknown number of targets using multiple sensors"
    - "marginal multi bernoulli filters rfs derivation of mht jipda and association based member"
    - "an efficient variational approximation of the best fitting multi bernoulli filter"

Connected through hyperedge HE-7 (induced by source paper "extended object tracking introduction overview and applications"):
  with members:
    - "second order extended kalman filter for extended object and group tracking"
    - "marginal multi bernoulli filters rfs derivation of mht jipda and association based member"
    - "bayesian inference via approximation of log likelihood for priors in exponential family"
    - "an efficient variational approximation of the best fitting multi bernoulli filter"
    - "extended object tracking with random hypersurface models"

Connected through hyperedge HE-8 (induced by source paper "multiple target tracking based on sets of trajectories"):
  with members:
    - "poisson multi bernoulli mixture filter direct derivation and implementation"
    - "a metric for sets of trajectories that is practical and mathematically consistent"
    - "a metric on the space of finite sets of trajectories for evaluation of multi target tracking algorithms"
    - "marginal multi bernoulli filters rfs derivation of mht jipda and association based member"

Question: Please tell me which class the center node 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.SY(Systems and Control)