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: "extraction of projection profile run histogram and entropy features straight from run length compressed text documents"
  Abstract: Document Image Analysis, like any Digital Image Analysis requires identification and extraction of proper features, which are generally extracted from uncompressed images, though in reality images are made available in compressed form for the reasons such as transmission and storage efficiency. However, this implies that the compressed image should be decompressed, which indents additional computing resources. This limitation induces the motivation to research in extracting features directly from the compressed image. In this research, we propose to extract essential features such as projection profile, run-histogram and entropy for text document analysis directly from run-length compressed text-documents. The experimentation illustrates that features are extracted directly from the compressed image without going through the stage of decompression, because of which the computing time is reduced. The feature values so extracted are exactly identical to those extracted from uncompressed images.

Connected through hyperedge HE-1 (induced by source paper "direct processing of document images in compressed domain"):
  with members:
    - "entropy computations of document images in run length compressed domain"
    - "automatic detection of font size straight from run length compressed text documents"
    - "direct processing of run length compressed document image for segmentation and characterization of a specified block"
    - "extraction of line word character segments directly from run length compressed printed text documents"

Connected through hyperedge HE-2 (induced by source paper "automatic detection of font size straight from run length compressed text documents"):
  with members:
    - "entropy computations of document images in run length compressed domain"
    - "direct processing of run length compressed document image for segmentation and characterization of a specified block"
    - "extraction of line word character segments directly from run length compressed printed text documents"

Connected through hyperedge HE-3 (induced by source paper "direct processing of run length compressed document image for segmentation and characterization of a specified block"):
  with members:
    - "entropy computations of document images in run length compressed domain"
    - "extraction of line word character segments directly from run length compressed printed text documents"

Connected through hyperedge HE-4 (induced by source paper "extraction of line word character segments directly from run length compressed printed text documents"):
  with members:
    - "text line segmentation of historical documents a survey"

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)