Foreground Object Structure Transfer for Unsupervised Domain Adaptation

no code implementations • 14 Sep 2021 • Jieren Cheng, Le Liu, Xiangyan Tang, Wenxuan Tu, Boyi Liu, Ke Zhou, Qiaobo Da, Yue Yang

In practice, since the label of the target domain is not available, we use the clustering information of the source domain to assign pseudo labels to the target domain samples, and then according to the source domain data prior knowledge guides those positive features to maximum the inter-class distance between different classes and mimimum the intra-class distance.

Clustering Object +1

Traffic Flow Combination Forecasting Method Based on Improved LSTM and ARIMA

no code implementations • 25 Jun 2019 • Boyi Liu, Xiangyan Tang, Jieren Cheng, Pengchao Shi

In this paper, we define the traffic data time singularity ratio in the dropout module and propose a combination prediction method based on the improved long short-term memory neural network and time series autoregressive integrated moving average model (SDLSTM-ARIMA), which is derived from the Recurrent Neural Networks (RNN) model.

Time Series Time Series Analysis +1