Artificial intelligence (AI) and machine learning (ML) have recently been radically improved
and are now being employed in almost every application domain to develop automated or …

The application of Artificial Intelligence (AI) and Machine Learning (ML) to cybersecurity
challenges has gained traction in industry and academia, partially as a result of widespread …

With the rapid advancements in the field of autonomous driving, the need for faster and more
accurate object detection frameworks has become a necessity. Many recent deep learning …

The remarkable success of deep learning has prompted interest in its application to medical
imaging diagnosis. Even though state-of-the-art deep learning models have achieved …

With the power of parallel processing, large datasets, and fast computational resources,
deep neural networks (DNNs) have outperformed highly trained and experienced human …

Current machine learning models have shown high efficiency in solving a wide variety of
real-world problems. However, their black box character poses a major challenge for the …

In this study, we train a convolutional neural network (CNN) model using a selection of
Coupled Model Intercomparison Project (CMIP) phase 5 and 6 models to investigate the …

Visual attribution (VA) in relation to medical images is an essential aspect of modern
automation-assisted diagnosis. Since it is generally not straightforward to obtain pixel-level …

Understanding the predictions made by Artificial Intelligence (AI) systems is becoming more
and more important as deep learning models are used for increasingly complex and high …

Due to the complexity of the etiology of autism spectrum disorders, the existing autism
diagnosis method is still based on scales. With the continuous development of artificial …