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: "moral lineage tracing"
  Abstract: Lineage tracing, the tracking of living cells as they move and divide, is a central problem in biological image analysis. Solutions, called lineage forests, are key to understanding how the structure of multicellular organisms emerges. We propose an integer linear program (ILP) whose feasible solutions define, for every image in a sequence, a decomposition into cells (segmentation) and, across images, a lineage forest of cells (tracing). In this ILP, path-cut inequalities enforce the morality of lineages, i.e., the constraint that cells do not merge. To find feasible solutions of this NP-hard problem, with certified bounds to the global optimum, we define efficient separation procedures and apply these as part of a branch-and-cut algorithm. To show the effectiveness of this approach, we analyze feasible solutions for real microscopy data in terms of bounds and run-time, and by their weighted edit distance to lineage forests traced by humans.

Connected through hyperedge HE-1 (induced by source paper "cell detection with star convex polygons"):
  with members:
    - "arbitrary oriented scene text detection via rotation proposals"
    - "multiclass weighted loss for instance segmentation of cluttered cells"
    - "mask r cnn"
    - "ssd single shot multibox detector"
    - "parsing images of overlapping organisms with deep singling out networks"
    - "dcan deep contour aware networks for accurate gland segmentation"
    - "straight to shapes real time detection of encoded shapes"
    - "you only look once unified real time object detection"

Connected through hyperedge HE-2 (induced by source paper "efficient algorithms for moral lineage tracing"):
  with members:
    - "the minimum cost connected subgraph problem in medical image analysis"
    - "arttrack articulated multi person tracking in the wild"
    - "lifting of multicuts"
    - "efficient decomposition of image and mesh graphs by lifted multicuts"
    - "fast planar correlation clustering for image segmentation"
    - "large scale correlation clustering optimization"

Connected through hyperedge HE-3 (induced by source paper "multi person pose estimation via column generation"):
  with members:
    - "deepercut a deeper stronger and faster multi person pose estimation model"
    - "arttrack articulated multi person tracking in the wild"
    - "deepcut joint subset partition and labeling for multi person pose estimation"
    - "tracking objects with higher order interactions using delayed column generation"

Connected through hyperedge HE-4 (induced by source paper "a message passing algorithm for the minimum cost multicut problem"):
  with members:
    - "a dual ascent framework for lagrangean decomposition of combinatorial problems"
    - "a new look at reweighted message passing"
    - "efficient decomposition of image and mesh graphs by lifted multicuts"
    - "a comparative study of modern inference techniques for structured discrete energy minimization problems"
    - "a multiscale framework for challenging discrete optimization"
    - "efficiently searching for frustrated cycles in map inference"

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.CV(Computer Vision and Pattern Recognition)