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4. As can be seen in the figure, each application of the convolution kernel filters out the part of the image that meets the conditions (the larger the activation value, the more qualified it is). However, the number of parameters remaining after applying the convolution operation is still ...
Microsoft uses machine learning and optimization to reduce E-Commerce fraud INFORMS Journal on Applied Analytics, 50 (1) (2020), pp. 64-79 CrossrefView in ScopusGoogle Scholar 12. E. Kurshan, H. Shen Graph computing for financial crime and fraud detection: Trends, challenges and outlook Inte...
The computational complexity needed for neural network analyses is considerably reduced compared to other algorithms and it also significantly improves computing precision. Concomitantly, the high fault tolerance of CNNs allows the use of incomplete or fuzzy background images, thereby effectively enhancing ...