Inspired by biological neurons, the activation functions play an essential part in the learning
process of any artificial neural network (ANN) commonly used in many real-world problems …

Artificial neural networks (ANN), typically referred to as neural networks, are a class of
Machine Learning algorithms and have achieved widespread success, having been …

The recent discovery of special human neocortical pyramidal neurons that can individually
learn the XOR function highlights the significant performance gap between biological and …

Activation functions are essential components in any neural network model; they play a
crucial role in determining the network's expressive power through their introduced non …

Abstract In Convolutional Neural Networks (CNNs), the selection and use of appropriate
activation functions is of critical importance. It has been seen that the Rectified Linear Unit …

Many industrial and real life problems exhibit highly nonlinear periodic behaviors and the
conventional methods may fall short of finding their analytical or closed form solutions. Such …

Activation functions play a decisive role in determining the capacity of Deep Neural
Networks as they enable neural networks to capture inherent nonlinearities present in data …

Dynamic networks offer an insight of how relational systems evolve. However, modeling
these networks efficiently remains a challenge, primarily due to computational constraints …

The concept of digital ownership is not new, and has been widely used in gaming contexts
to allow players to customize their experiences via profile pictures, skins, upgrades and add …

Abstract Machine learning is penetrating various domains virtually, thereby proliferating
excellent results. It has also found an outlet in digital forensics, wherein it is becoming the …