Background Brain cancer is a destructive and life-threatening disease that imposes
immense negative effects on patients' lives. Therefore, the detection of brain tumors at an …

The learning process and hyper-parameter optimization of artificial neural networks (ANNs)
and deep learning (DL) architectures is considered one of the most challenging machine …

Recently, many metaheuristic optimization algorithms have been developed to address real-
world issues. In this study, a new physics-based metaheuristic called Fick's law optimization …

Abstract Convolutional Neural Network (CNN) is a prevalent topic in deep learning (DL)
research for their architectural advantages. CNN relies heavily on hyperparameter …

The field of medical image processing plays a significant role in brain tumor classification.
The survival rate of patients can be increased by diagnosing the tumor at an early stage …

Recent advances in online payment technologies combined with the impact of the COVID-
19 global pandemic has led to a significant escalation in the number of online transactions …

Swarm intelligence techniques have been created to respond to theoretical and practical
global optimization problems. This paper puts forward an enhanced version of the firefly …

Deep learning has recently been utilized with great success in a large number of diverse
application domains, such as visual and face recognition, natural language processing …

One of the worst diseases is a brain tumor, which is defined by abnormal development of
synapses in the brain. Early detection of brain tumors is essential for improving prognosis …

Breast cancer is a significant health concern due to its aggressive nature and high mortality
rates. Early detection is crucial to improving patient outcomes. Thermography, a non …