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: "real time dense stereo embedded in a uav for road inspection"
  Abstract: The condition assessment of road surfaces is essential to ensure their serviceability while still providing maximum road traffic safety. This paper presents a robust stereo vision system embedded in an unmanned aerial vehicle (UAV). The perspective view of the target image is first transformed into the reference view, and this not only improves the disparity accuracy, but also reduces the algorithm's computational complexity. The cost volumes generated from stereo matching are then filtered using a bilateral filter. The latter has been proved to be a feasible solution for the functional minimisation problem in a fully connected Markov random field model. Finally, the disparity maps are transformed by minimising an energy function with respect to the roll angle and disparity projection model. This makes the damaged road areas more distinguishable from the road surface. The proposed system is implemented on an NVIDIA Jetson TX2 GPU with CUDA for real-time purposes. It is demonstrated through experiments that the damaged road areas can be easily distinguished from the transformed disparity maps.

Connected through hyperedge HE-1 (induced by source paper "pt resnet perspective transformation based residual network for semantic road image segmentation"):
  with members:
    - "pothole detection based on disparity transformation and road surface modeling"
    - "a robust pavement mapping system based on normal constrained stereo visual odometry"
    - "key ingredients of self driving cars"
    - "road damage detection based on unsupervised disparity map segmentation"
    - "scene understanding networks for autonomous driving based on around view monitoring system"
    - "a general pipeline for 3d detection of vehicles"
    - "road surface 3d reconstruction based on dense subpixel disparity map estimation"
    - "real time stereo vision based lane detection system"

Connected through hyperedge HE-2 (induced by source paper "a robust pavement mapping system based on normal constrained stereo visual odometry"):
  with members:
    - "pothole detection based on disparity transformation and road surface modeling"
    - "a robust roll angle estimation algorithm based on gradient descent"
    - "key ingredients of self driving cars"
    - "road damage detection based on unsupervised disparity map segmentation"
    - "road surface 3d reconstruction based on dense subpixel disparity map estimation"
    - "a novel disparity transformation algorithm for road segmentation"
    - "vins mono a robust and versatile monocular visual inertial state estimator"
    - "orb slam2 an open source slam system for monocular stereo and rgb d cameras"

Connected through hyperedge HE-3 (induced by source paper "robust lane marking detection algorithm using drivable area segmentation and extended slt"):
  with members:
    - "pothole detection based on disparity transformation and road surface modeling"
    - "key ingredients of self driving cars"
    - "road damage detection based on unsupervised disparity map segmentation"
    - "real time subpixel fast bilateral stereo"
    - "road surface 3d reconstruction based on dense subpixel disparity map estimation"
    - "real time stereo vision based lane detection system"
    - "a novel disparity transformation algorithm for road segmentation"
    - "multiple lane detection algorithm based on optimised dense disparity map estimation"

Connected through hyperedge HE-4 (induced by source paper "road crack detection using deep convolutional neural network and adaptive thresholding"):
  with members:
    - "using dp towards a shortest path problem related application"
    - "real time subpixel fast bilateral stereo"
    - "road surface 3d reconstruction based on dense subpixel disparity map estimation"
    - "real time stereo vision based lane detection system"
    - "real time stereo vision for road surface 3 d reconstruction"
    - "a novel disparity transformation algorithm for road segmentation"
    - "improving computer aided detection using convolutional neural networks and random view aggregation"
    - "improving object detection with deep convolutional networks via bayesian optimization and structured prediction"

Connected through hyperedge HE-5 (induced by source paper "road damage detection based on unsupervised disparity map segmentation"):
  with members:
    - "pothole detection based on disparity transformation and road surface modeling"
    - "road surface 3d reconstruction based on dense subpixel disparity map estimation"
    - "real time stereo vision based lane detection system"
    - "real time stereo vision for road surface 3 d reconstruction"
    - "a novel disparity transformation algorithm for road segmentation"
    - "rethinking atrous convolution for semantic image segmentation"
    - "deep residual learning for image recognition"

Connected through hyperedge HE-6 (induced by source paper "a robust roll angle estimation algorithm based on gradient descent"):
  with members:
    - "real time subpixel fast bilateral stereo"
    - "road surface 3d reconstruction based on dense subpixel disparity map estimation"
    - "real time stereo vision based lane detection system"
    - "real time stereo vision for road surface 3 d reconstruction"
    - "a novel disparity transformation algorithm for road segmentation"
    - "multiple lane detection algorithm based on optimised dense disparity map estimation"

Connected through hyperedge HE-7 (induced by source paper "autonomous uav landing system based on visual navigation"):
  with members:
    - "pothole detection based on disparity transformation and road surface modeling"
    - "key ingredients of self driving cars"
    - "road damage detection based on unsupervised disparity map segmentation"
    - "road surface 3d reconstruction based on dense subpixel disparity map estimation"

Connected through hyperedge HE-8 (induced by source paper "a novel dual lidar calibration algorithm using planar surfaces"):
  with members:
    - "vins mono a robust and versatile monocular visual inertial state estimator"
    - "focal loss in 3d object detection"
    - "voxelnet end to end learning for point cloud based 3d object detection"
    - "extrinsic calibration of 3d range finder and camera without auxiliary object or human intervention"

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)