… exciting new advances in machine learning, specifically “deep learning”. Deep learning, ie
as deep neural networks, has been a rapidly growing subfield of machine learning. The main …

Recently, deep learning (DL) has emerged as a revolutionary and versatile tool transforming
industry applications and generating new and improved capabilities for scientific discovery …

… deep learning has been broadly applied. In particular, we demonstrate that deep learning has
advanced … Furthermore, we note advances in algorithmic and architectural mechanisms in …

… This review paper presents the state of the art in deep learning to highlight the major challenges
and … Deep learning has also picked up the pace due to the hardware advancements of …

… advances in deep learning applications. It was also undertaken to review the issues … in
deep learning such as unsupervised learning, black-box models, and online learning and …

… [66] provide a thoroughly survey on deep learning based object detection frameworks. …
a systematic and comprehensive review of deep learning-based algorithms that handle small …

… Stanford uses a deep learning method to classify skin cancer diseases. Still, ML advances
… The main aim of the chapter is to study the advancement of ML in recent healthcare applica…

… In recent years, deep learning algorithms have … deep learning models which save time
and produce accurate results. This research aims to emphasize the impact of deep learning …

… In this paper, the state-of-the-art in surface defect inspection using deep learning is … ,
and learning-based methods. Third, we investigate recent advances in deep learning-based …

… In this section, we thoroughly summarize the advanced studies on deep learning-based
brain signals (table 4). The hybrid models are divided into three parts: the combination of RNN …