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 "abmof a novel optical flow algorithm for dynamic vision sensors"):
  Abstract: Dynamic Vision Sensors (DVS), which output asynchronous log intensity change events, have potential applications in high-speed robotics, autonomous cars and drones. The precise event timing, sparse output, and wide dynamic range of the events are well suited for optical flow, but conventional optical flow (OF) algorithms are not well matched to the event stream data. This paper proposes an event-driven OF algorithm called adaptive block-matching optical flow (ABMOF). ABMOF uses time slices of accumulated DVS events. The time slices are adaptively rotated based on the input events and OF results. Compared with other methods such as gradient-based OF, ABMOF can efficiently be implemented in compact logic circuits. Results show that ABMOF achieves comparable accuracy to conventional standards such as Lucas-Kanade (LK). The main contributions of our paper are new adaptive time-slice rotation methods that ensure the generated slices have sufficient features for matching,including a feedback mechanism that controls the generated slices to have average slice displacement within the block search range. An LK method using our adapted slices is also implemented. The ABMOF accuracy is compared with this LK method on natural scene data including sparse and dense texture, high dynamic range, and fast motion exceeding 30,000 pixels per second.The paper dataset and source code are available from this http URL

Includes members:
  Member "vertical landing for micro air vehicles using event based optical flow":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "evolved neuromorphic control for high speed divergence based landings of mavs")
  Member "event based 6 dof camera tracking from photometric depth maps":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "globally optimal contrast maximisation for event based motion estimation")
  Member "the event camera dataset and simulator event based data for pose estimation visual odometry and slam":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "eventsr from asynchronous events to image reconstruction restoration and super resolution via end to end adversarial learning")
  Member "flownet 2 0 evolution of optical flow estimation with deep networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "learning video object segmentation from unlabeled videos")
  Member "steering a predator robot using a mixed frame event driven convolutional neural network":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "event based vision a survey")

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)