… deep learning (DL) algorithms—a subset of ML algorithms largely inspired by the
cognitive system’s ability to observe, analyze, learn, … algorithm outcomes as deep learning–augmented …

… challenge for the data-hungry methods of deep learning: How … when data are scarce and
opportunities to test models are … trends, challenges, and opportunities in applications of deep-…

… challenges is the ability to process information at massively superior speed and accuracy.
Despite large-scale success of deep learning … to the current deep learning paradigm, research …

… applied deep learning to prevalent construction challenges … survey of the applications of
deep learning techniques within the … techniques of deep learning to numerous challenges in the …

… Learning (ML) as a noteworthy subset of AI. ML empowers computers to analyze extensive
datasets, while Deep Learning (… Within our work, we outline key challenges that both current …

… For food drying research, supervised learning such deep learning neural network are widely
used due to its unique advantages to handling the complex food drying problem. ANN can …

… offers marketing researchers countless opportunities to better predict and … challenges in
data management and measurement in the era of digital data and the role of machine learning …

… Since then, advances in deep learning have enabled computer vision to grow immensely
and it has found applications in almost every field from medicine to defense, to transportation …

… 2.1 Opportunities Our experimentation with these deep learning and computer vision
techniques revealed significant opportunities but also substantial challenges in the prospective …

… In this section, we briefly review relevant deep learning algorithms that were originally …
research into deep learning in SAR. In addition, we mention the latest deep learning developments…