… new Swish activation function, introduces Swish function into the … multi-layer small-size
convolution module instead of large-size convolution module in the convolution neural network to …

… adopts a multi-layer GRU neural network structure to capture the internal connection between
the historical epidemic data to achieve better prediction effect. The structure diagram is as …

With the rapid development of the functional applications of portable and wearable electronic
products (such as curved smartphones, smartwatches, laptops, and electronic skins), there …

… ℃) dynamic viscosity),the micro/nano-scale structure with high resolution and high aspect
ratio was fabricated by multi-layer stacking on three kinds of paper substrates.For example,the …

… multi-layer neural networks, convolutional neural networks, long-short term memory neural
networks and neural networks … and believe that deep neural network will be the main method …

… In this review, on the basis of the mechanisms underlying Li dendrite formation and growth,
strategies for constructing various functional SEI films, highlights in structure and property of …

The method of strict slope threshold algorithm is not sufficient to achieve complex object
identification or ground features classification from LiDAR data. In this research, artificial …

… A typical neuron in neural networks A typical multi-layer neural network model … ▶ A new
model for learning in graph domains ▶ The graph neural network model ▶ Spectral networks …

Metal oxide semiconductor (MOS) gas sensors have been widely used in military and scientific
research, as well as various industries; this is because of the unique advantages of MOS …

The emergence of generative adversarial networks is another milestone in the field of
computer vision. It provides a new tool for solving various image prediction problems. For this …