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 "three dimensional reconstruction of botanical trees with simulatable geometry"):
  Abstract: We tackle the challenging problem of creating full and accurate three dimensional reconstructions of botanical trees with the topological and geometric accuracy required for subsequent physical simulation, e.g. in response to wind forces. Although certain aspects of our approach would benefit from various improvements, our results exceed the state of the art especially in geometric and topological complexity and accuracy. Starting with two dimensional RGB image data acquired from cameras attached to drones, we create point clouds, textured triangle meshes, and a simulatable and skinned cylindrical articulated rigid body model. We discuss the pros and cons of each step of our pipeline, and in order to stimulate future research we make the raw and processed data from every step of the pipeline as well as the final geometric reconstructions publicly available.

Includes members:
  Member "seeing tree structure from vibration":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "cloth in the wind a case study of physical measurement through simulation")
  Member "data augmented contact model for rigid body simulation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "tossingbot learning to throw arbitrary objects with residual physics")
  Member "iterative deep learning for road topology extraction":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deep vessel segmentation by learning graphical connectivity")
  Member "combining learned and analytical models for predicting action effects":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "omnipush accurate diverse real world dataset of pushing dynamics with rgb d video")
  Member "beyond the pixel wise loss for topology aware delineation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "improving image autoencoder embeddings with perceptual loss")
  Member "joint 2d 3d semantic data for indoor scene understanding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "3d point cloud processing and learning for autonomous driving")
  Member "perceptual losses for real time style transfer and super resolution":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "gan compression efficient architectures for interactive conditional gans")
  Member "u net convolutional networks for biomedical image segmentation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "secure and robust machine learning for healthcare a survey")

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)