|
|
|
|
|
Huihui Li, Linfeng Gou, Huacong Li and Zhidan Liu
Sensor health assessments are of great importance for accurately understanding the health of an aeroengine, supporting maintenance decisions, and ensuring flight safety. This study proposes an intelligent framework based on a physically guided neural net...
ver más
|
|
|
|
|
|
|
|
|
Chunwei Hu, Xianfeng Liu, Sheng Wu, Fei Yu, Yongkun Song and Jin Zhang
Accurate crowd flow prediction is essential for traffic guidance and traffic control. However, the high nonlinearity, temporal complexity, and spatial complexity that crowd flow data have makes this problem challenging. This research proposes a dynamic g...
ver más
|
|
|
|
|
|
|
|
|
Xinjing Zhang and Qixun Zhou
Human pose estimation, as the basis of advanced computer vision, has a wide application perspective. In existing studies, the high-capacity model based on the heatmap method can achieve accurate recognition results, but it encounters many difficulties wh...
ver más
|
|
|
|
|
|
|
|
|
Lichao Sun, Yunyun Dong, Shuang Xu, Xiufang Feng and Xiaole Fan
Epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma (KRAS) are the most common driver genes in non-small cell lung cancer patients. However, frequent gene mutation testing raises a potential risk of cancer metastasis. In our paper, a Mut-SeRe...
ver más
|
|
|
|
|
|
|
|
|
Dibo Dong, Shangwei Wang, Qiaoying Guo, Xing Li, Weibin Zou and Zicheng You
Accurately predicting wind speed is crucial for the generation efficiency of offshore wind energy. This paper proposes an ultra-short-term wind speed prediction method using a graph neural network with a multi-head attention mechanism. The methodology ai...
ver más
|
|
|
|