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: "let s get dirty gan based data augmentation for soiling and adverse weather classification in autonomous driving"
  Abstract: Cameras are getting more and more important in autonomous driving. Wide-angle fisheye cameras are relatively cheap sensors and very suitable for automated parking and low-speed navigation tasks. Four of such cameras form a surround-view system that provides a complete and detailed view around the vehicle. These cameras are usually directly exposed to harsh environmental settings and therefore can get soiled very easily by mud, dust, water, frost, etc. The soiling on the camera lens has a direct impact on the further processing of the images they provide. While adverse weather conditions, such as rain, are getting attention recently, there is limited work on lens soiling. We believe that one of the reasons is that it is difficult to build a diverse dataset for this task, which is moreover expensive to annotate. We propose a novel GAN based algorithm for generating artificial soiling data along with the corresponding annotation masks. The manually annotated soiling dataset and the generated augmentation dataset will be made public. We demonstrate the generalization of our fisheye trained soiling GAN model on the Cityscapes dataset. Additionally, we provide an empirical evaluation of the degradation of the semantic segmentation algorithm with the soiled data.

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)