… of applications of Machine Learning and Deep Learning technologies in Agriculture. We
also highlight opportunities therein and the potentials and challenges, particularly in Nigeria. …

… rate affect the generalization performance; (iii) how can we derive much sharper analysis
of practical SGD for finding a global minimizer of deep learning with good generalization …

… 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. …

… Moreover, we discuss the challenges and trade-offs involved in building machine
learning models for digital mental health and highlight potential future work in this direction. …

… 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. …

… They also discussed the challenges for the deep learning. … The challenges offered by big
data were timely and provided many opportunities and searches for the deep learning. Gheisari …

… Deep learning applications can be divided into medical imaging analysis and applications
… Deep learning is considered a subbranch of ML which depends on neural networks for …

… Deep learning Serving system (LDS). This survey aims to summarize and categorize the
emerging challenges and optimization opportunities for large-scale deep learning serving …

… Histopathology images, given their data complexity and density are ideally suited for
interrogation via deep learning approaches since they attempt to use deep architectures to …

… came when a convolutional network won this challenge for the first time and by a wide margin,
… The years ahead are full of challenges and opportunities to improve deep learning even …