Deep convolutional neural networks (DCNNs) have achieved impressive performance in
image recognition, object detection, etc. Nevertheless, they are susceptible to adversarial …

Small data sets make develo** calibration models using deep neural networks difficult
because it is easy to overfit the system. We developed two deep neural network …

Accurately predicting the trajectories of nearby vehicles is a crucial and complex task in
autonomous driving due to the inherent uncertainty in driving behavior. Multimodal trajectory …

Dealing with significant class imbalance poses a significant challenge in various real-world
applications, particularly when the accurate classification and generalization of minority …

Pile running during the installation of offshore large diameter pipe piles poses a significant
challenge to construction safety and pile bearing capacity. This paper proposes a deep …

Deep neural networks (DNN) have been widely used in SAR image Target recognition and
have achieved great success. However, the black box attribute of DNN makes the …