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 "segmentation of nearly isotropic overlapped tracks in photomicrographs using successive erosions as watershed markers"):
  Abstract: The major challenges of automatic track counting are distinguishing tracks and material defects, identifying small tracks and defects of similar size, and detecting overlapping tracks. Here we address the latter issue using WUSEM, an algorithm which combines the watershed transform, morphological erosions and labeling to separate regions in photomicrographs. WUSEM shows reliable results when used in photomicrographs presenting almost isotropic objects. We tested this method in two datasets of diallyl phthalate (DAP) photomicrographs and compared the results when counting manually and using the classic watershed. The mean automatic/manual efficiency ratio when using WUSEM in the test datasets is 0.97 +/- 0.11.

Includes members:
  Member "imagej2 imagej for the next generation of scientific image data":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "computational analysis of laminar structure of the human cortex based on local neuron features")
  Member "jansen midas a multi level photomicrograph segmentation software based on isotropic undecimated wavelets":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "skeletracks automatic separation of overlapping fission tracks in apatite and muscovite using image processing")
  Member "scikit image image processing in python":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "surveiledge real time video query based on collaborative cloud edge deep learning")
  Member "an automatic method for segmentation of fission tracks in epidote crystal photomicrographs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "jansen midas a multi level photomicrograph segmentation software based on isotropic undecimated wavelets")
  Member "the numpy array a structure for efficient numerical computation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a deep unsupervised feature learning spiking neural network with binarized classification layers for emnist classification")

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)