Space Objects Classification Techniques : A Survey

被引:0
|
作者
Jahirabadkar, Sunita [1 ]
Narsay, Prajakta [1 ]
Pharande, Shivani [1 ]
Deshpande, Gargi [1 ]
Kitture, Anusha [1 ]
机构
[1] Cummins Coll Engn Women, Dept Comp Engn, Pune, Maharashtra, India
关键词
Deep Neural Networks (DNN); Convolutional Neural Network (CNN); Light Curves; Long/Short Term Memory (LSTM); Spaces Debris;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Space debris is a collection of some natural meteoroids or manmade objects floating in space. The amount of space debris has risen tremendously over the last few years. Due to their high (8km per sec) velocity, these debris cause a major threat to active space missions. For surveillance of active satellites, Space Situational Awareness is one of the important fields to be studied. Hence, to protect active satellites, it is important to classify the space objects as debris and apply collision avoidance techniques. This paper presents a survey on various approaches being used for classification of space objects using light curves as a differentiating characteristic. Classification of space objects based on k-nearest neighbour algorithms and various Deep Learning algorithms such as Convolutional Neural Network (CNN) or Recurrent Neural Network (RNN) is researched.
引用
下载
收藏
页码:786 / 791
页数:6
相关论文
共 50 条
  • [41] Artificial Intelligence Techniques for Classification of Eye Tumors: A Survey
    Allam, Esraa
    Alfonse, Marco
    Salem, Abdel-Badeeh M.
    5TH INTERNATIONAL CONFERENCE ON COMPUTING AND INFORMATICS (ICCI 2022), 2022, : 175 - 179
  • [42] Survey on Botnet Detection Techniques: Classification, Methods, and Evaluation
    Xing, Ying
    Shu, Hui
    Zhao, Hao
    Li, Dannong
    Guo, Li
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2021, 2021
  • [43] Watermarking Techniques for Relational Databases: Survey, Classification and Comparison
    Halder, Raju
    Pal, Shantanu
    Cortesi, Agostino
    JOURNAL OF UNIVERSAL COMPUTER SCIENCE, 2010, 16 (21) : 3164 - 3190
  • [44] A Survey of Deep Learning Techniques for Underwater Image Classification
    Mittal, Sparsh
    Srivastava, Srishti
    Jayanth, J. Phani
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 34 (10) : 6968 - 6982
  • [45] A Survey of Outlier Detection Techniques in IoT: Review and Classification
    Al Samara, Mustafa
    Bennis, Ismail
    Abouaissa, Abdelhafid
    Lorenz, Pascal
    JOURNAL OF SENSOR AND ACTUATOR NETWORKS, 2022, 11 (01)
  • [46] An Advanced Classification of Cloud Computing Security Techniques: A Survey
    Alturfi, Sabah M.
    Al-Musawi, Bahaa
    Marhoon, Haydar Abdulameer
    8TH INTERNATIONAL CONFERENCE ON APPLIED SCIENCE AND TECHNOLOGY (ICAST 2020), 2020, 2290
  • [47] A survey on classification techniques for opinion mining and sentiment analysis
    Hemmatian, Fatemeh
    Sohrabi, Mohammad Karim
    ARTIFICIAL INTELLIGENCE REVIEW, 2019, 52 (03) : 1495 - 1545
  • [48] Analyzing Brain Tumor Classification Techniques: A Comprehensive Survey
    Chauhan, Pratikkumar
    Lunagaria, Munindra
    Verma, Deepak Kumar
    Vaghela, Krunal
    Diwan, Anjali
    Patole, Shashikant P.
    Mahadeva, Rajesh
    IEEE ACCESS, 2024, 12 : 136389 - 136407
  • [49] A Survey of Blind Modulation Classification Techniques for OFDM Signals
    Kumar, Anand
    Majhi, Sudhan
    Gui, Guan
    Wu, Hsiao-Chun
    Yuen, Chau
    SENSORS, 2022, 22 (03)
  • [50] Deep Learning Techniques for Diabetic Retinopathy Classification: A Survey
    Atwany, Mohammad Z.
    Sahyoun, Abdulwahab H.
    Yaqub, Mohammad
    IEEE ACCESS, 2022, 10 : 28642 - 28655