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 "road network and travel time extraction from multiple look angles with spacenet data"):
  Abstract: Identification of road networks and optimal routes directly from remote sensing is of critical importance to a broad array of humanitarian and commercial applications. Yet while identification of road pixels has been attempted before, estimation of route travel times from overhead imagery remains a novel problem, particularly for off-nadir overhead imagery. To this end, we extract road networks with travel time estimates from the SpaceNet MVOI dataset. Utilizing the CRESIv2 framework, we demonstrate the ability to extract road networks in various observation angles and quantify performance at 27 unique nadir angles with the graph-theoretic APLS_length and APLS_time metrics. A minimal gap of 0.03 between APLS_length and APLS_time scores indicates that our approach yields speed limits and travel times with very high fidelity. We also explore the utility of incorporating all available angles during model training, and find a peak score of APLS_time = 0.56. The combined model exhibits greatly improved robustness over angle-specific models, despite the very different appearance of road networks at extremely oblique off-nadir angles versus images captured from directly overhead.

Includes members:
  Member "city scale road extraction from satellite imagery v2 road speeds and travel times":
    also connected through other hyperedges:
      (none)
  Member "spacenet mvoi a multi view overhead imagery dataset":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "isaid a large scale dataset for instance segmentation in aerial images")
  Member "spacenet a remote sensing dataset and challenge series":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "deepsat v2 feature augmented convolutional neural nets for satellite image classification")
  Member "from satellite imagery to disaster insights":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "tackling climate change with machine learning")
  Member "deep learning in agriculture a survey":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "driver drowsiness detection model using convolutional neural networks techniques for android application")
  Member "benchmark dataset for automatic damaged building detection from post hurricane remotely sensed imagery":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "xbd a dataset for assessing building damage from satellite imagery")
  Member "the cityscapes dataset for semantic urban scene understanding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "gan compression efficient architectures for interactive conditional gans")
  Member "a large dataset of object scans":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "deep non line of sight reconstruction")

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)