… Deep learning is widely used in many fields including autonomous driving cars [19], diabetic
blood glucose prediction [78], and software engineering [18, 20, 21, 52, 63, 87, 114, 117, …

… Notably, DL-enabled, advanced-analytics framework can open new opportunities for smart
… Finally, we provide different research challenges and future trends for DL-based IIoT. …

… In this Perspective, we assess the opportunities and challenges presented by this new wave
… theory as a deep learning problem. We assess extant evidence that deep networks form …

… opportunities for novel methods in earth environmental monitoring have emerged. Deep
learning (DL)… tool focusing on large-size and deep artificial neural networks. The DL models can …

… As machine learning or deep learning applications are an ever-… it in deep learning networks.
This is happening even though there are many opportunities as well as risks deep learning …

… AI has developed from ML to deep learning to applied AI. A machine’s ability to learn from
experience, adapt to new inputs, and perform specific tasks without human intervention is …

… Recently, deep learning (DL) approaches have solved several real-world problems of
complex nature. However, their strengths in terms of control processes for AD have not been …

… Motivated by this consideration, the contribution of this paper is to investigate the deep learning
… of deep learning models in healthcare solutions to bridge deep learning techniques and …

… deep networks for supervised or discriminative learning, unsupervised or generative learning
as well as hybrid learning … world application areas where deep learning techniques can be …

… and discuss how they address the aforementioned challenges. We further discuss a set
of possible future opportunities and new perspectives on addressing the challenges. …