Research on Vision of Intelligent Car Based on Broad Learning System

Article Properties
Cite
Liu, Xiang, and Yuanqing Wu. “Research on Vision of Intelligent Car Based on Broad Learning System”. IEEE Transactions on Cybernetics, vol. 53, no. 8, 2023, pp. 4805-14, https://doi.org/10.1109/tcyb.2021.3137801.
Liu, X., & Wu, Y. (2023). Research on Vision of Intelligent Car Based on Broad Learning System. IEEE Transactions on Cybernetics, 53(8), 4805-4814. https://doi.org/10.1109/tcyb.2021.3137801
Liu, Xiang, and Yuanqing Wu. “Research on Vision of Intelligent Car Based on Broad Learning System”. IEEE Transactions on Cybernetics 53, no. 8 (2023): 4805-14. https://doi.org/10.1109/tcyb.2021.3137801.
Liu X, Wu Y. Research on Vision of Intelligent Car Based on Broad Learning System. IEEE Transactions on Cybernetics. 2023;53(8):4805-14.
Journal Categories
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Technology
Electrical engineering
Electronics
Nuclear engineering
Electronics
Technology
Mechanical engineering and machinery
Refrences
Title Journal Journal Categories Citations Publication Date
Visualizing and understanding convolutional networks 2014
Very deep convolutional networks for large-scale image recognition 2014
Automatic target recognition by matching oriented edge pixels IEEE Transactions on Image Processing
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
  • Technology: Engineering (General). Civil engineering (General)
 103 1997
10.1109/TCYB.2016.2588526
Random vector functional link neural network based ensemble deep learning Pattern Recognition
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks
  • Technology: Mechanical engineering and machinery
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
  • Technology: Engineering (General). Civil engineering (General)
 99 2021
Citations
Title Journal Journal Categories Citations Publication Date
Twin Broad Learning System for Fault Diagnosis of Rotating Machinery IEEE Transactions on Instrumentation and Measurement
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks
  • Science: Mathematics: Instruments and machines
  • Technology: Engineering (General). Civil engineering (General)
 2023
Citations Analysis
Category Category Repetition
Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks1
Science: Mathematics: Instruments and machines1
Technology: Engineering (General). Civil engineering (General)1
The category Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks 1 is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Twin Broad Learning System for Fault Diagnosis of Rotating Machinery and was published in 2023. The most recent citation comes from a 2023 study titled Twin Broad Learning System for Fault Diagnosis of Rotating Machinery. This article reached its peak citation in 2023, with 1 citations. It has been cited in 1 different journals. Among related journals, the IEEE Transactions on Instrumentation and Measurement cited this research the most, with 1 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year