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: "rodnet object detection under severe conditions using vision radio cross modal supervision"
  Abstract: Radar is usually more robust than the camera in severe autonomous driving scenarios, e.g., weak/strong lighting and bad weather. However, the semantic information from the radio signals is difficult to extract. In this paper, we propose a radio object detection network (RODNet) to detect objects purely from the processed radar data in the format of range-azimuth frequency heatmaps (RAMaps). To train the RODNet, we introduce a cross-modal supervision framework, which utilizes the rich information extracted by a vision-based object 3D localization technique to teach object detection for the radar. In order to train and evaluate our method, we build a new dataset -- CRUW, containing synchronized video sequences and RAMaps in various scenarios. After intensive experiments, our RODNet shows favorable object detection performance without the presence of the camera. To the best of our knowledge, this is the first work that can achieve accurate multi-class object detection purely using radar data as the input.

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)