In this paper we make use of two highly efficient second order neural network training algorithms, namely the LMAM (Levenberg-Marquardt with Adaptive ...
Two highly efficient second order neural network training algorithms are used, namely the LMAM and OLMAM, for the construction of an efficient pap-smear ...
In this paper we make use of two highly efficient second order neural network training algorithms, namely the LMAM (Levenberg-Marquardt with Adaptive ...
In this paper we make use of two highly efficient second order neural network training algorithms, namely the LMAM (Levenberg-Marquardt with Adaptive ...
In this paper we make use of two highly efficient second or- der neural network training algorithms, namely the LMAM (Levenberg-. Marquardt with Adaptive ...
A new learning algorithm is introduced that can deal with incomplete data. The algorithm uses a multi-granulation ensemble of classifiers approach. Firstly, the ...
The RF, DT, adaptive boosting, and gradient boosting algorithms yielded the maximum classification score of 100% for the prediction of cervical cancer. SVM, on ...
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The detection of cervical cancer cells uses an ANN for classifying the normal and abnormal cells in the cervix region of the uterus.
Jun 29, 2021 · In this paper, we presented a single-cell CPS image classification model using pre-trained deep convolutional neural network algorithms. The pre ...
Second order algorithms are very efficient for neural network training because of their fast convergence. In traditional Implementations of second order.
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