… Machine learning (ML) and deep learning (DL) applications have recently gained popularity
… We conclude our study with a critical discussion of the challenges and opportunities in …

… In this chapter, we discuss state-of-the-art deep learning … a discussion of the challenges
of deep learning methods with … We conclude that there are unlimited opportunities for the …

… opportunities derived from new technologies and architectures. Further, it presents our view
of the ecosystem that will enable deep learning … all these challenges and opportunities blend …

… Section 4 to highlight how deep learning techniques could help … The applied method,
commonly used in deep learning and … deep learning (DL) can help to overcome these challenges. …

… One of the specific areas of ML is deep learning (DL). In recent years, there has been an
increased interest in research in this area. It can be illustrated by the number of publications in …

This study investigates, through a narrative review, the transformative impact of deep
learning (DL) in the field of radiotherapy, particularly in light of the accelerated developments …

… in several domains, and Deep Learning (DL) has attracted … of state-of-the-art Deep Learning
(DL) solutions for Air Traffic … identifying opportunities, and highlighting open challenges to …

… For this purpose it employs a deep learning (DL) model to … Google Colaboratory enables
us to run a deep learning (DL) … and subsequently, the opportunities and challenges are also …

… deep learning in the back-end simulation flows. This paper discusses a few challenges that
the deployment of deep learning … and the corresponding opportunities for future research. …

… deep learning models. This paper posits that TDL may complement graph representation
learning and geometric deep learning … choice for various machine learning settings. To this end…