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 "oct fingerprints resilience to presentation attacks"):
  Abstract: Optical coherent tomography (OCT) fingerprint technology provides rich depth information, including internal fingerprint (papillary junction) and sweat (eccrine) glands, in addition to imaging any fake layers (presentation attacks) placed over finger skin. Unlike 2D surface fingerprint scans, additional depth information provided by the cross-sectional OCT depth profile scans are purported to thwart fingerprint presentation attacks. We develop and evaluate a presentation attack detector (PAD) based on deep convolutional neural network (CNN). Input data to CNN are local patches extracted from the cross-sectional OCT depth profile scans captured using THORLabs Telesto series spectral-domain fingerprint reader. The proposed approach achieves a TDR of 99.73% @ FDR of 0.2% on a database of 3,413 bonafide and 357 PA OCT scans, fabricated using 8 different PA materials. By employing a visualization technique, known as CNN-Fixations, we are able to identify the regions in the OCT scan patches that are crucial for fingerprint PAD detection.

Includes members:
  Member "grad cam visual explanations from deep networks via gradient based localization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "causal interpretability for machine learning problems methods and evaluation")
  Member "universal material translator towards spoof fingerprint generalization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fingerprint spoof generalization")
  Member "livdet in action fingerprint liveness detection competition 2019":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fingerprint spoof generalization")
  Member "livdet 2017 fingerprint liveness detection competition 2017":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "biometric presentation attack detection beyond the visible spectrum")
  Member "fingerprint presentation attack detection generalization and efficiency":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fingerprint spoof generalization")
  Member "raspireader open source fingerprint reader":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "fingerprint spoof generalization")
  Member "review of the fingerprint liveness detection livdet competition series 2009 to 2015":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "biometric presentation attack detection beyond the visible spectrum")
  Member "cnn fixations an unraveling approach to visualize the discriminative image regions":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a tour of convolutional networks guided by linear interpreters")

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)