Neural networks have proven to be a highly effective tool for solving complex problems in
many areas of life. Recently, their importance and practical usability have further been …

Deep learning researchers have a keen interest in proposing two new novel activation
functions which can boost network performance. A good choice of activation function can …

Well production forecasting has a very important guiding significance for oilfield production
and management. The traditional BP neural network is difficult to deal with the data with time …

Well-known activation functions like ReLU or Leaky ReLU are non-differentiable at the
origin. Over the years, many smooth approximations of ReLU have been proposed using …

Data collection using thermocouple sensors in low-cost data acquisition is prone to noise
interference, which could reduce the data quality. Noise sources such as cold junction …

Merení genové exprese je nezbytné pro porozumení bunecným procesum a stavum v
rozlicných experimentálních podmínkách, což je potreba v ruzných oblastech …

Merení genové exprese je nezbytné pro porozumení bunecným procesum a stavum v
rozlicných experimentálních podmínkách, což je potreba v ruzných oblastech …

Delineating associations between images and covariates is a central aim of imaging studies.
To tackle this problem, we propose a novel non-parametric approach in the framework of …

An activation function is a crucial component of a neural network that introduces non-
linearity in the network. The state-of-the-art performance of a neural network depends on the …