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- W2950022897 abstract "Neural Networks, with their remarkable capacity to get significance from convoluted information can be utilized to remove patterns that are too composite to be in any way seen by humans. A prepared neural network can be thought of as a specialist in the classification of data which is given to analyze. There are different kinds of Neural Networks like Artificial Neural Network (ANN), Feedforward Neural Network, Recurrent Neural Network(RNN), Recursive Recurrent Neural Network (RRNN), Convolutional Neural Network(CNN), Modular Neural Network (MNN), Restricted Boltzmann Machine (RBM) etc. In this paper, we have discussed the performance of ANN, CNN, RNN, and RBM where CNN has outplayed the remaining with accuracy of 97.81%." @default.
- W2950022897 created "2019-06-27" @default.
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- W2950022897 date "2019-03-01" @default.
- W2950022897 modified "2023-09-26" @default.
- W2950022897 title "Comparative Analysis on variants of Neural Networks: An Experimental Study" @default.
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- W2950022897 doi "https://doi.org/10.1109/icaccs.2019.8728327" @default.
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