Neural networks are pre-trained on ImageNet dataset for Pap stained single cell and whole-slide image classification ... framework achieves a classification accuracy of 98.55% and sensitivity ...

Researchers have developed a deep learning-based method that can predict the possible onset of Alzheimer’s disease from brain images with an accuracy ... achieving the best classification accuracy of ...

The model's accuracy is 91.00 percent so 91 of the 100 test ... is usually much faster than the more common sgd (stochastic gradient descent) algorithm for DNN image classification. In Keras ...

In their latest paper published in Light: Science & Applications, UCLA team reports a leapfrog advance in D2NN-based image classification accuracy ... iterative pruning algorithm, so that the ...

The study found that deep learning models, especially CNNs, were the most frequently implemented technique (61.2%), followed ...

The technology, which incorporates deep learning models, could be used in "smart" vehicles, robotics and image ... algorithms have been capable of optimizing the trade-off between detection ...

The report’s authors used the ResNet image classification model to assess how long it takes algorithms to achieve a high level of accuracy. In October 2017, 13 days of training time were ...

Researchers have developed a deep learning-based method that can predict the possible onset of Alzheimer’s disease from brain images with an accuracy ... achieving the best classification accuracy of ...