… the impact of machine learning and deep learning on employment and the workforce.
While these technologies have the potential to create new job opportunities, they also pose a …

… of deep learning, also, this article aims to provide a more detailed overview of the most
significant facets of deep learning… of deep learning and the various deep learning techniques and …

… with deep learning models, the final PdM stage that is essential for implementing PdM
systems. Moreover, state-of-the-art deep learning … Finally, open challenges and possible future …

… In this Section, a physics-informed deep learning (DL) approach for enhanced visual inspection
… by a demonstration of impact diagnosis using a physics-informed deep learning model. …

… deep learning, investigates the application of these methods in reinforcement learning, and
highlights the fundamental research challenges and directions associated with the UQ field. …

… underlying theory of some of the most recent deep learning methods, and finally, attempts
to identify new opportunities in tool condition monitoring, toward the realization of Industry 4.0. …

… • We identify the limitations and deficiencies of deep learning approaches when being applied
to the … We find that deep learning methods are utilized to integrate features and reduce …

… The first systematic review was published of deep learning performance in detecting
diseases from medical imaging45—this showed that deep learning models perform similarly to …

… Deep Learning (DL) has had an immense success in the recent past, leading to state-of-the-…
In this survey, we perform a broad and thorough investigation on challenges, techniques …

… Supervised Deep Learning (DL) algorithms can be widely … detection solely on unsupervised
deep learning algorithms. Also, … We see that Deep Learning using massive neural networks …