Real-time, accurate and comprehensive traffic flow data is the key of intelligent
transportation systems to provide efficient services for urban transportation. In the process of …

Short-term predictions of wind power and its ramp events play a critical role in economic
operation and risk management of smart grid. This paper proposes a hybrid forecasting …

Generating photos satisfying multiple constraints finds broad utility in the content creation
industry. A key hurdle to accomplishing this task is the need for paired data consisting of all …

Automatic seizure detection technology is of great significance to reduce workloads of
neurologists for epilepsy diagnosis and treatments. Imbalanced classification is a challenge …

Currently, with the rapid development of deep learning, many breakthroughs have been
made in the field of facial expression recognition (FER). However, according to our prior …

A significant robustness gap exists between machine intelligence and human perception
despite recent advances in deep learning. Deep learning is not provably secure. A critical …

Although image inpainting is a challenging task in computer vision, most existing image
inpainting methods have achieved remarkable progress. However, occlusion and low …

Ballistic impacts are a primary risk in both civil and military defence applications, where
successfully predicting the dynamic response of a material or structure to impact crucial to …

Deep neural network approaches have made remarkable progress in many machine
learning tasks. However, the latest research indicates that they are vulnerable to adversarial …

In this chapter, we aim to scale-up the operation of GAN using recurrent neural network
(RNN). The GAN is designed with two deep neural network models, where the first network …