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: "multiresolution mapping and informative path planning for uav based terrain monitoring"
  Abstract: Unmanned aerial vehicles (UAVs) can offer timely and cost-effective delivery of high-quality sensing data. How- ever, deciding when and where to take measurements in complex environments remains an open challenge. To address this issue, we introduce a new multiresolution mapping approach for informative path planning in terrain monitoring using UAVs. Our strategy exploits the spatial correlation encoded in a Gaussian Process model as a prior for Bayesian data fusion with probabilistic sensors. This allows us to incorporate altitude-dependent sensor models for aerial imaging and perform constant-time measurement updates. The resulting maps are used to plan information-rich trajectories in continuous 3-D space through a combination of grid search and evolutionary optimization. We evaluate our framework on the application of agricultural biomass monitoring. Extensive simulations show that our planner performs better than existing methods, with mean error reductions of up to 45% compared to traditional "lawnmower" coverage. We demonstrate proof of concept using a multirotor to map color in different environments.

Connected through hyperedge HE-1 (induced by source paper "building an aerial ground robotics system for precision farming"):
  with members:
    - "semantic mapping for orchard environments by merging two sides reconstructions of tree rows"
    - "agricolmap aerial ground collaborative 3d mapping for precision farming"
    - "maplab an open framework for research in visual inertial mapping and localization"
    - "fully convolutional networks with sequential information for robust crop and weed detection in precision farming"
    - "build your own visual inertial drone a cost effective and open source autonomous drone"
    - "an informative path planning framework for uav based terrain monitoring"
    - "an effective multi cue positioning system for agricultural robotics"
    - "weedmap a large scale semantic weed mapping framework using aerial multispectral imaging and deep neural network for precision farming"

Connected through hyperedge HE-2 (induced by source paper "obstacle aware adaptive informative path planning for uav based target search"):
  with members:
    - "voxblox incremental 3d euclidean signed distance fields for on board mav planning"
    - "a decision theoretic approach to detection based target search with a uav"
    - "you only look once unified real time object detection"
    - "a tutorial on bayesian optimization of expensive cost functions with application to active user modeling and hierarchical reinforcement learning"

Connected through hyperedge HE-3 (induced by source paper "informative path planning and mapping for active sensing under localization uncertainty"):
  with members:
    - "bayesian optimisation for safe navigation under localisation uncertainty"
    - "sampling based incremental information gathering with applications to robotic exploration and environmental monitoring"
    - "an informative path planning framework for uav based terrain monitoring"

Connected through hyperedge HE-4 (induced by source paper "informative path planning for active field mapping under localization uncertainty"):
  with members:
    - "bayesian optimisation for safe navigation under localisation uncertainty"
    - "sampling based incremental information gathering with applications to robotic exploration and environmental monitoring"
    - "an informative path planning framework for uav based terrain monitoring"

Connected through hyperedge HE-5 (induced by source paper "an informative path planning framework for uav based terrain monitoring"):
  with members:
    - "sampling based incremental information gathering with applications to robotic exploration and environmental monitoring"
    - "hindsight is only 50 50 unsuitability of mdp based approximate pomdp solvers for multi resolution information gathering"
    - "a data driven approach for autonomous motion planning and control in off road driving scenarios"
    - "algorithms for semantic segmentation of multispectral remote sensing imagery using deep learning"
    - "dynamic system identification and control for a cost effective open source vtol mav"
    - "weednet dense semantic weed classification using multispectral images and mav for smart farming"
    - "modeling curiosity in a mobile robot for long term autonomous exploration and monitoring"
    - "pomdp lite for robust robot planning under uncertainty"

Connected through hyperedge HE-6 (induced by source paper "kriging based robotic exploration for soil moisture mapping using a cosmic ray sensor"):
  with members:
    - "sampling based incremental information gathering with applications to robotic exploration and environmental monitoring"

Connected through hyperedge HE-7 (induced by source paper "weednet dense semantic weed classification using multispectral images and mav for smart farming"):
  with members:
    - "build your own visual inertial odometry aided cost effective and open source autonomous drone"
    - "peduncle detection of sweet pepper for autonomous crop harvesting combined color and 3 d information"
    - "automatic model based dataset generation for fast and accurate crop and weeds detection"
    - "control of a quadrotor with reinforcement learning"
    - "the cityscapes dataset for semantic urban scene understanding"
    - "deeplab semantic image segmentation with deep convolutional nets atrous convolution and fully connected crfs"
    - "boxsup exploiting bounding boxes to supervise convolutional networks for semantic segmentation"
    - "segnet a deep convolutional encoder decoder architecture for image segmentation"

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)