Neural networks have shown tremendous growth in recent years to solve numerous
problems. Various types of neural networks have been introduced to deal with different types …

In recent years, deep learning has garnered tremendous success in a variety of application
domains. This new field of machine learning has been growing rapidly and has been …

Integrating artificial intelligence with food category recognition has been a field of interest for
research for the past few decades. It is potentially one of the next steps in revolutionizing …

We propose $\textit {Mish} $, a novel self-regularized non-monotonic activation function
which can be mathematically defined as: $ f (x)= x\tanh (softplus (x)) $. As activation …

Deep neural networks have been successfully used in diverse emerging domains to solve
real world complex problems with may more deep learning (DL) architectures, being …

In neural networks literature, there is a strong interest in identifying and defining activation
functions which can improve neural network performance. In recent years there has been a …

Deep learning has demonstrated tremendous success in variety of application domains in
the past few years. This new field of machine learning has been growing rapidly and applied …

Wildfires are a worldwide natural disaster causing important economic damages and loss of
lives. Experts predict that wildfires will increase in the coming years mainly due to climate …

Through the success of deep learning in various domains, artificial neural networks are
currently among the most used artificial intelligence methods. Taking inspiration from the …

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 …