human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "multiplierless 16 point dct approximation for low complexity image and video coding"):
  Abstract: An orthogonal 16-point approximate discrete cosine transform (DCT) is introduced. The proposed transform requires neither multiplications nor bit-shifting operations. A fast algorithm based on matrix factorization is introduced, requiring only 44 additions—the lowest arithmetic cost in literature. To assess the introduced transform, computational complexity, similarity with the exact DCT, and coding performance measures are computed. Classical and state-of-the-art 16-point low-complexity transforms were used in a comparative analysis. In the context of image compression, the proposed approximation was evaluated via PSNR and SSIM measurements, attaining the best cost–benefit ratio among the competitors. For video encoding, the proposed approximation was embedded into a HEVC reference software for direct comparison with the original HEVC standard. Physically realized and tested using FPGA hardware, the proposed transform showed 35 and 37 % improvements of area-time and area-time-squared VLSI metrics when compared to the best competing transform in the literature.

Includes members:
  Member "an orthogonal 16 point approximate dct for image and video compression":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on basis images for the digital image representation")
  Member "improved 8 point approximate dct for image and video compression requiring only 14 additions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "capstone mobility modeling on smartphones to achieve privacy by design")
  Member "dct like transform for image compression requires 14 additions only":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "low complexity image and video coding based on an approximate discrete tchebichef transform")
  Member "a digital hardware fast algorithm and fpga based prototype for a novel 16 point approximate dct for image compression applications":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "an orthogonal 16 point approximate dct for image and video compression")
  Member "a dct approximation for image compression":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "low complexity image and video coding based on an approximate discrete tchebichef transform")

Question: Please tell me which class the source paper 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)