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: "visual perception and modelling in unstructured orchard for apple harvesting robots"
  Abstract: Vision perception and modelling are the essential tasks of robotic harvesting in the unstructured orchard. This paper develops a framework of visual perception and modelling for robotic harvesting of fruits in the orchard environments. The developed framework includes visual perception, scenarios mapping, and fruit modelling. The Visual perception module utilises a deep-learning model to perform multi-purpose visual perception task within the working scenarios; The scenarios mapping module applies OctoMap to represent the multiple classes of objects or elements within the environment; The fruit modelling module estimates the geometry property of objects and estimates the proper access pose of each fruit. The developed framework is implemented and evaluated in the apple orchards. The experiment results show that visual perception and modelling algorithm can accurately detect and localise the fruits, and modelling working scenarios in real orchard environments. The $F_{1}$ score and mean intersection of union of visual perception module on fruit detection and segmentation are 0.833 and 0.852, respectively. The accuracy of the fruit modelling in terms of centre localisation and pose estimation are 0.955 and 0.923, respectively. Overall, an accurate visual perception and modelling algorithm are presented in this paper.

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)