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 "augmented memory for correlation filters in real time uav tracking"):
  Abstract: The outstanding computational efficiency of discriminative correlation filter (DCF) fades away with various complicated improvements. Previous appearances are also gradually forgotten due to the exponential decay of historical views in traditional appearance updating scheme of DCF framework, reducing the model's robustness. In this work, a novel tracker based on DCF framework is proposed to augment memory of previously appeared views while running at real-time speed. Several historical views and the current view are simultaneously introduced in training to allow the tracker to adapt to new appearances as well as memorize previous ones. A novel rapid compressed context learning is proposed to increase the discriminative ability of the filter efficiently. Substantial experiments on UAVDT and UAV123 datasets have validated that the proposed tracker performs competitively against other 26 top DCF and deep-based trackers with over 40 FPS on CPU.

Includes members:
  Member "can a robot become a movie director learning artistic principles for aerial cinematography":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "keyfilter aware real time uav object tracking")
  Member "learning aberrance repressed correlation filters for real time uav tracking":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "keyfilter aware real time uav object tracking")
  Member "towards a robust aerial cinematography platform localizing and tracking moving targets in unstructured environments":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "learning visuomotor policies for aerial navigation using cross modal representations")
  Member "boundary effect aware visual tracking for uav with online enhanced background learning and multi frame consensus verification":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "keyfilter aware real time uav object tracking")
  Member "target aware deep tracking":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "siamese box adaptive network for visual tracking")
  Member "the unmanned aerial vehicle benchmark object detection and tracking":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "mini unmanned aerial vehicle based remote sensing techniques applications and prospects")
  Member "learning spatial temporal regularized correlation filters for visual tracking":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "keyfilter aware real time uav object tracking")
  Member "kernel cross correlator":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "keyfilter aware real time uav object tracking")

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)