Deep Learning is the most widely used tool in the contemporary field of computer vision. Its
ability to accurately solve complex problems is employed in vision research to learn deep …

Deep learning applies multiple processing layers to learn representations of data with
multiple levels of feature extraction. This emerging technique has reshaped the research …

Deep learning is at the heart of the current rise of artificial intelligence. In the field of
computer vision, it has become the workhorse for applications ranging from self-driving cars …

Due to the rapid growth in network traffic and increasing security threats, Intrusion Detection
Systems (IDS) have become increasingly critical in the field of cyber security for providing …

The outstanding performance of deep neural networks has promoted deep learning
applications in a broad set of domains. However, the potential risks caused by adversarial …

Marine target detection technology plays an important role in sea surface monitoring, sea
area management, ship collision avoidance, and other fields. Traditional marine target …

As we seek to deploy machine learning models beyond virtual and controlled domains, it is
critical to analyze not only the accuracy or the fact that it works most of the time, but if such a …

Real-world data is often unbalanced and long-tailed, but deep models struggle to recognize
rare classes in the presence of frequent classes. To address unbalanced data, most studies …

The performance of a biometric system that relies on a single biometric modality (eg,
fingerprints only) is often stymied by various factors such as poor data quality or limited …

Face recognition has achieved great success in the last five years due to the development of
deep learning methods. However, deep convolutional neural networks (DCNNs) have been …