Dropout training is a relatively new algorithm which appears to be highly effective for improving the quality of neural network predictions. It's not yet widely implemented in neural network API ...

Deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are designed to ...

After the training process is completed, the demo displays the values of the neural network's 59 weights and biases that were determined by the training process. The demo finishes by computing the ...

While humans concentrate on the meaning of objects, artificial intelligence focuses on visual characteristics.

The ability to precisely predict movements is essential not only for humans and animals, but also for many AI applications - from autonomous driving to robotics. Researchers at the Technical ...

According to Intel, PaddlePaddle was also the first framework to integrate Vector Neural Network Instructions (VNNI). These new enhancements deliver dramatic performance improvements for image ...

During training, the neural network adjusts the weights of the synapses so that an input produces the desired output. Here, in more detail, is how the process works: The first layer of neurons ...

Deep convolutional neural networks (DCNNs) don't see objects the way humans do -- using configural shape perception -- and that could be dangerous in real-world AI applications. The study employed ...