Monitoring the growth conditions and behavior of fish will enable scientific management,
reduce the threat of losses caused by disease and stress. Traditional monitoring methods are …

… and effective deep learning algorithms have been developed. The purpose of this paper
is to categorize and evaluate different image tagging approaches based on deep learning …

… feedforward networks was revived around 2006 (refs 31,32,33,34) by a group of
researchers brought together by the Canadian Institute for Advanced Research (CIFAR). The …

… In addition to the image field, deep learning methods have also enabled advances in the …
Deep learning is based on models of neural networks with many hidden layers, known as deep …

… However, many recent advances, typically the methods for the last 5 years, are not …
Compared with the previous survey, we pay more attention to deep learning-based methods. In …

… including low-cost depth camera and advanced machine learning technologies. In this paper,
we present a complete overview of deep learning based methodologies for sign language …

… learning and contemporary deep learning applications. The first part briefly discusses the
classical machine learning … the use of modern deep learning algorithms. The proposed …

… that deep learning architecture. For these reasons, our review article discusses the most
recent challenges of deep vision systems in terms of deep learning … of advanced deep learning …

… deep learning is also summarized for MD simulations. Furthermore, IML is introduced for the
deep learning … Our paper deals with an interesting topic about deep learning applications of …

… Since the impact of machine learning in dermatology will increase in the next few years, the
goal of this paper is to critically review the latest advances in this field as well as to reflect on …