To See in the Dark: N2DGAN for Background Modeling in Nighttime Scene

no code implementations • 12 Dec 2019 • Zhenfeng Zhu, Yingying Meng, Deqiang Kong, Xingxing Zhang, Yandong Guo, Yao Zhao

Due to the deteriorated conditions of \mbox{illumination} lack and uneven lighting, nighttime images have lower contrast and higher noise than their daytime counterparts of the same scene, which limits seriously the performances of conventional background modeling methods.

EA-LSTM: Evolutionary Attention-based LSTM for Time Series Prediction

no code implementations • 9 Nov 2018 • Youru Li, Zhenfeng Zhu, Deqiang Kong, Hua Han, Yao Zhao

To address this issue, an evolutionary attention-based LSTM training with competitive random search is proposed for multivariate time series prediction.

Time Series Time Series Prediction