Recent research has employed chemical reaction networks (CRNs), which harness biochemical processes for computations that translate interactions involving biochemical species into graphical form.

By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.

For decades, scientists have looked to light as a way to speed up computing. Photonic neural networks—systems that use light ...

Experimental results show that the proposed vCNN improves proving performance by 20-fold for a simple MNIST and 18,000-fold for VGG16. The security of the proposed scheme is formally proven.

A deep convolutional neural network is used to extract high-order morphological features from binary images to distinguish textured microstructures from untextured microstructures. The convolutional ...

To effectively monitor and control the fermentation process, an accurate real-time measurement of important variables is necessary. However, given the complexity of microbial fermentation and the ...

This article studies the meaning of parameters of fully connected neural networks with single hidden layer from the perspective of spectrum. Under the constraints of numerical range, the corresponding ...