Deep neural networks have attained great success in handling high dimensional data,
especially images. However, generating naturalistic images containing ginormous subjects …

Generative adversarial networks (GANs), a novel framework for training generative models
in an adversarial setup, have attracted significant attention in recent years. The two …

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 …

Research on facial expression recognition (FER) technology can promote the development
of theoretical and practical applications for our daily life. Currently, most of the related works …

We present a 3D deep learning framework that can generate a complete cranial model
using a defective one. The Boolean subtraction between these two models generates the …

An efficient, appliance-level approach for energy disaggregation, exploiting the benefits of
Generative Adversarial Networks, is presented. The concept of adversarial training supports …

Completing a corrupted image by filling in correct structures and reasonable textures for a
complex scene remains an elusive challenge. In case that a missing hole involves diverse …

Most recently-proposed face completion algorithms use high-level features extracted from
convolutional neural networks (CNNs) to recover semantic texture content. Although the …

Cyber-Physical-Social Systems (CPSS) offer a new perspective for applying advanced
information technology to improve urban transportation. However, real-world traffic datasets …

The imputation of time series traffic flow data is of great significance to the intelligent
transportation, urban planning, and road emergency handling. This paper proposes a filling …