Efficient algorithms to mine frequent patterns are crucial to many tasks in data mining. Since the Apriori algorithm was proposed in 1994, there have been several methods proposed to improve its performance. However, most still adopt its candidate set generation-and-test approach. In addition, many methods do not generate all frequent patterns, making them inadequate to derive association rules...

Identification via face recognition offers enormous advantages to both civilian and criminal detection programs. A next generation system that has the potential to recognize such wanted criminals from a large dataset considered to be used for security of the public safety. It also has the prospective to provide high data rates at low power over various illumination conditions in the, to be iden...

Large-scale integration of photovoltaics (PV) into electricity grids is challenged by the intermittent nature solar power. Sky-image-based forecasting using deep learning has been recognized as a promising approach to predicting short-term fluctuations. However, there are few publicly available standardized benchmark datasets for image-based forecasting, which limits comparison different models...

With the development of infrared technology, dim and small target detection plays a vital role in precision guidance applications. To address problems insufficient dataset coverage huge actual shooting costs methods, this paper proposes method for generating sequence datasets based on generative adversarial networks (GANs). Specifically, first, improved deep convolutional network (DCGAN) model ...