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 "oreos oriented recognition of 3d point clouds in outdoor scenarios"):
  Abstract: We introduce a novel method for oriented place recognition with 3D LiDAR scans. A Convolutional Neural Network is trained to extract compact descriptors from single 3D LiDAR scans. These can be used both to retrieve near-by place candidates from a map, and to estimate the yaw discrepancy needed for bootstrapping local registration methods. We employ a triplet loss function for training and use a hard-negative mining strategy to further increase the performance of our descriptor extractor. In an evaluation on the NCLT and KITTI datasets, we demonstrate that our method outperforms related state-of-the-art approaches based on both data-driven and handcrafted data representation in challenging long-term outdoor conditions.

Includes members:
  Member "segmap 3d segment mapping using data driven descriptors":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "3d dynamic scene graphs actionable spatial perception with places objects and humans")
  Member "a comprehensive review of 3d point cloud descriptors":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "3d point cloud processing and learning for autonomous driving")
  Member "pointnetvlad deep point cloud based retrieval for large scale place recognition":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "review deep learning on 3d point clouds")
  Member "voxelnet end to end learning for point cloud based 3d object detection":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "review deep learning on 3d point clouds")
  Member "segmatch segment based place recognition in 3d point clouds":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "segmap segment based mapping and localization using data driven descriptors")
  Member "locnet global localization in 3d point clouds for mobile vehicles":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "segmap segment based mapping and localization using data driven descriptors")
  Member "image similarity using deep cnn and curriculum learning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "getnet get target area for image pairing")
  Member "cnn for imu assisted odometry estimation using velodyne lidar":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "cae lo lidar odometry leveraging fully unsupervised convolutional auto encoder for interest point detection and feature description")

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)