Analysis and presenting the educational techniques in Machine and Deep Learning Short communication

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    This paper gives a present of general learning of deep methodology and its applications to a variety of signal and data processing schedules. It is discussed about Machine learning vs. Deep Learning a brief and which is best suited in the market, Dissimilarities, Problem handling, Interpretability, Comparative and different options between cubic centimeter and metric capacity unit and concluded by justifying deep learning is a part of Machine learning and Machine learning is a part of Artificial intelligence.

     

     


  • Keywords


    Artificial Intelligence; Cubic centimeter; Deep learning; Machine Learning; Metric Capacity.

  • References


      [1] “Machine Learning for Image Reconstruction” Ge Wang, Jong Chu Ye, Klaus Mueller, Jeffrey A. Fessler May 2, 2018.

      [2] Temporal Dynamics of Learning for Resolution of super video: A Learning of deep Approach Ding Liu, Student Member, IEEE, Zhaowen Wang, Member, IEEE, Yuchen Fan, Xianming Liu, Zhangyang Wang, Member, IEEE, Shiyu Chang, Xinchao Wang, and Thomas S. Huang, Life Fellow, IEEE.

      [3] Intelligent tuninf of parameter in Optimization-based Iterative CT Reconstruction via Deep Reinforcement Learning Chenyang Shen, Yesenia Gonzalez, Liyuan Chen, Steve B. Jiang, Xun Jia.

      [4] Deep Learning: Applications and Methods Li Deng, Microsoft Research. One Microsoft Way Redmond, WA 98052, USA deng@microsoft.com, Dong Yu, Microsoft Research, One Microsoft way Redmond, WA 98052, USA, Dong.Yu@microsoft.com

      [5] Deep Monocular Depth Estimation via Integration of Global and Local Predictions Youngjung Kim, Student Member, IEEE, Hyungjoo Jung, Student Member, IEEE, Dongbo Min, Senior Member, IEEE, and Kwanghoon Sohn, Senior Member, IEEE.

      [6] Image Reconstruction Is a New Frontier of Machine Learning— Editorial for the Special Issue


 

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Article ID: 20716
 
DOI: 10.14419/ijet.v7i4.6.20716




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