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 "learning to take good pictures of people with a robot photographer"):
  Abstract: We present a robotic system capable of navigating autonomously by following a line and taking good quality pictures of people. When a group of people are detected, the robot rotates towards them and then back to line while continuously taking pictures from different angles. Each picture is processed in the cloud where its quality is estimated in a two-stage algorithm. First, features such as the face orientation and likelihood of facial emotions are input to a fully connected neural network to assign a quality score to each face. Second, a representation is extracted by abstracting faces from the image and it is input to a to Convolutional Neural Network (CNN) to classify the quality of the overall picture. We collected a dataset in which a picture was labeled as good quality if subjects are well-positioned in the image and oriented towards the camera with a pleasant expression. Our approach detected the quality of pictures with 78.4% accuracy in this dataset and received a better mean user rating (3.71/5) than a heuristic method that uses photographic composition procedures in a study where 97 human judges rated each picture. A statistical analysis against the state-of-the-art verified the quality of the resulting pictures.

Includes members:
  Member "yolov3 an incremental improvement":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "perception and decision making of autonomous systems in the era of learning an overview")
  Member "wider face a face detection benchmark":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "generalizing face representation with unlabeled data")

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.RO(Robotics)