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: "sketch2code transformation of sketches to ui in real time using deep neural network"
  Abstract: User Interface (UI) prototyping is a necessary step in the early stages of application development. Transforming sketches of a Graphical User Interface (UI) into a coded UI application is an uninspired but time-consuming task performed by a UI designer. An automated system that can replace human efforts for straightforward implementation of UI designs will greatly speed up this procedure. The works that propose such a system primarily focus on using UI wireframes as input rather than hand-drawn sketches. In this paper, we put forward a novel approach wherein we employ a Deep Neural Network that is trained on our custom database of such sketches to detect UI elements in the input sketch. Detection of objects in sketches is a peculiar visual recognition task that requires a specific solution that our deep neural network model attempts to provide. The output from the network is a platform-independent UI representation object. The UI representation object is a dictionary of key-value pairs to represent the UI elements recognized along with their properties. This is further consumed by our UI parser which creates code for different platforms. The intrinsic platform-independence allows the model to create a UI prototype for multiple platforms with single training. This two-step approach without the need for two trained models improves over other methods giving time-efficient results (average time: 129 ms) with good accuracy.

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)