… , a comprehensive literature review on these graph-based deep learning architectures in …
survey on graph-based deep learning works in traffic domain. Note that some works we review …

… This article surveys recent developments in deep learning based object detectors. Concise
overview of benchmark datasets and evaluation metrics used in detection is also provided …

… survey the current state-of-the-art on deep learning technologies used in autonomous driving.
We start by presenting AI-based … this survey, we review the different AI and deep learning …

… deep learning techniques for detecting small objects in images. We provide a comprehensive
review … We identify and analyze major challenges and summarize strategies for improving …

… collaborative filtering and content-based filtering, RL is able to … since the introduction of
deep reinforcement learning (DRL), … In this paper, a survey on reinforcement learning based …

… to gain a deep insight on how machine learning can benefit … survey on data fusion methods
based on machine learning. … of data fusion and machine learning in terms of definitions, …

… of deep learning algorithms. Then, we provide the frontiers of applying deep learning for
non-invasive brain signals analysis, by … Moreover, upon the deep learning-powered brain signal …

… 2 describes the research methodology adopted in this study. … research challenges, and
the future research scope are provided in Section 7. Finally, Section 8 concludes this review …

… machine learning algorithms and deep learning … in this study, traditional algorithms and
learning-based algorithms, as shown in Figure 1. Most of the traditional algorithms are based on …

… We address this limitation by presenting an evidence-based study that uses machine learning
algorithms to generate actionable insights of strategic value from this data-driven paradigm…