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: "unmanned aerial vehicles uavs a survey on civil applications and key research challenges"
  Abstract: The use of unmanned aerial vehicles (UAVs) is growing rapidly across many civil application domains, including real-time monitoring, providing wireless coverage, remote sensing, search and rescue, delivery of goods, security and surveillance, precision agriculture, and civil infrastructure inspection. Smart UAVs are the next big revolution in the UAV technology promising to provide new opportunities in different applications, especially in civil infrastructure in terms of reduced risks and lower cost. Civil infrastructure is expected to dominate more than $45 Billion market value of UAV usage. In this paper, we present UAV civil applications and their challenges. We also discuss the current research trends and provide future insights for potential UAV uses. Furthermore, we present the key challenges for UAV civil applications, including charging challenges, collision avoidance and swarming challenges, and networking and security-related challenges. Based on our review of the recent literature, we discuss open research challenges and draw high-level insights on how these challenges might be approached.

Connected through hyperedge HE-1 (induced by source paper "mini unmanned aerial vehicle based remote sensing techniques applications and prospects"):
  with members:
    - "learning to calibrate straight lines for fisheye image rectification"
    - "resource allocation for solar powered uav communication systems"
    - "throughput maximization for laser powered uav wireless communication systems"
    - "learning attraction field representation for robust line segment detection"
    - "anisotropic scale junction detection and matching for indoor images"
    - "deepmvs learning multi view stereopsis"
    - "the uavid dataset for video semantic segmentation"
    - "geonet unsupervised learning of dense depth optical flow and camera pose"

Connected through hyperedge HE-2 (induced by source paper "towards reliable uav swarm communication in d2d enhanced cellular network"):
  with members:
    - "cellular connected uav uplink association power control and interference coordination"
    - "ultra reliable and low latency wireless communication tail risk and scale"
    - "multi beam uav communication in cellular uplink cooperative interference cancellation and sum rate maximization"
    - "the sky is not the limit lte for unmanned aerial vehicles"
    - "ultra reliable uav communication using altitude and cooperation diversity"
    - "ultra reliable and low latency communications in 5g downlink physical layer aspects"
    - "uplink cooperative noma for cellular connected uav"
    - "a d2d based protocol for ultra reliable wireless communications for industrial automation"

Connected through hyperedge HE-3 (induced by source paper "connectivity aware uav path planning with aerial coverage maps"):
  with members:
    - "mobile networks connected drones field trials simulations and design insights"
    - "learning to communicate in uav aided wireless networks map based approaches"
    - "the sky is not the limit lte for unmanned aerial vehicles"
    - "a tutorial on uavs for wireless networks applications challenges and open problems"
    - "cellular enabled uav communication trajectory optimization under connectivity constraint"

Connected through hyperedge HE-4 (induced by source paper "micro air vehicle link mavlink in a nutshell a survey"):
  with members:
    - "sim4cv a photo realistic simulator for computer vision applications"
    - "airsim high fidelity visual and physical simulation for autonomous vehicles"

Connected through hyperedge HE-5 (induced by source paper "plane an extensible open source framework for modeling the internet of drones"):
  with members:
    - "internet of drones"

Connected through hyperedge HE-6 (induced by source paper "challenges of reliability assessment and enhancement in autonomous systems"):
  with members:
    - "tolerating soft errors in processor cores using clear cross layer exploration for architecting resilience"

Connected through hyperedge HE-7 (induced by source paper "design challenges of multi uav systems in cyber physical applications a comprehensive survey and future directions"):
  with members:
    - "oil observational imitation learning"
    - "uplink coverage performance of an underlay drone cell for temporary events"
    - "a tutorial on uavs for wireless networks applications challenges and open problems"
    - "ultra low power deep learning powered autonomous nano drones"
    - "a survey of machine and deep learning methods for internet of things iot security"
    - "how hard is it to cross the room training recurrent neural networks to steer a uav"
    - "prospect theory for enhanced cyber physical security of drone delivery systems a network interdiction game"
    - "the blockchain a new framework for robotic swarm systems"

Connected through hyperedge HE-8 (induced by source paper "mini uav based remote sensing techniques applications and prospectives"):
  with members:
    - "resource allocation for solar powered uav communication systems"
    - "throughput maximization for laser powered uav wireless communication systems"
    - "anisotropic scale junction detection and matching for indoor images"
    - "deepmvs learning multi view stereopsis"
    - "geonet unsupervised learning of dense depth optical flow and camera pose"
    - "hierarchical motion consistency constraint for efficient geometrical verification in uav image matching"
    - "image stitching by line guided local warping with global similarity constraint"
    - "the highd dataset a drone dataset of naturalistic vehicle trajectories on german highways for validation of highly automated driving systems"

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.RO(Robotics)