Pop-HSTM is a global-local coupled deep learning framework for dynamic population prediction that combines local spatial interaction learning, ConvLSTM and Temporal Transformer …
This study proposes a framework that integrates deep learning with co-occurrence theory to classify public emotions from social media data into single, dominant-subordinate, and …
Lunar craters are important geomorphological features, that provide valuable insights into lunar morphology, geology, and impact processes. However, the current understanding of …