Detection and classification of pneumonia using novel Superior Exponential (SupEx) activation function in convolutional neural networks

Many diseases threaten human health in many ways. Pneumonia is accepted as one of the most important health problems and causes of death worldwide. Therefore, deep learning techniques are used to solve problems in various fields, including diagnosing pneumonia. Convolutional neural networks (CNN), an artificial intelligence technique, are widely used in many areas such as segmentation, classification, signal processing. In deep networks, activation functions have an import. In CNN architectures, while the activation functions (AFs) are being developed, the activation functions are developed by taking into account the features such as not getting stuck in the local minimum of the CNN model and increasing the training performance. In the literature, although the ReLU is used in most studies, ReLU faces the problem that negative weights cannot be added to the network. To overcome the problem, the effect …