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 "deploying deep neural networks in the embedded space"):
  Abstract: Recently, Deep Neural Networks (DNNs) have emerged as the dominant model across various AI applications. In the era of IoT and mobile systems, the efficient deployment of DNNs on embedded platforms is vital to enable the development of intelligent applications. This paper summarises our recent work on the optimised mapping of DNNs on embedded settings. By covering such diverse topics as DNN-to-accelerator toolflows, high-throughput cascaded classifiers and domain-specific model design, the presented set of works aim to enable the deployment of sophisticated deep learning models on cutting-edge mobile and embedded systems.

Includes members:
  Member "f cnn text x a toolflow for mapping multiple convolutional neural networks on fpgas":
    also connected through other hyperedges:
      (none)
  Member "toolflows for mapping convolutional neural networks on fpgas a survey and future directions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "recurrent neural networks an embedded computing perspective")
  Member "approximate fpga based lstms under computation time constraints":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "long short term memory networks in memristor crossbar arrays")
  Member "dronet efficient convolutional neural network detector for real time uav applications":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "edgenet balancing accuracy and performance for edge based convolutional neural network object detectors")
  Member "cascadecnn pushing the performance limits of quantisation":
    also connected through other hyperedges:
      (none)
  Member "toward low flying autonomous mav trail navigation using deep neural networks for environmental awareness":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "aggressive perception aware navigation using deep optical flow dynamics and pixelmpc")
  Member "fpgaconvnet a toolflow for mapping diverse convolutional neural networks on embedded fpgas":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "toolflows for mapping convolutional neural networks on fpgas a survey and future directions")
  Member "mask r cnn":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "relatext exploiting visual relationships for arbitrary shaped scene text detection with graph convolutional networks")

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)