no code implementations • 27 Nov 2023 • Jialin Liu, Lu Yan, Xiaowei Liu, Yuzhuo Dai, Fanggen Lu, Yuanting Ma, Muzhou Hou, Zheng Wang
We conducted image processing of HRM to predict the esophageal contraction vigor for assisting the evaluation of esophageal dynamic function.
no code implementations • 24 Jul 2023 • Menglin Kong, Ruichen Li, Fan Liu, Xingquan Li, Juan Cheng, Muzhou Hou, Cong Cao
Landslide is a natural disaster that can easily threaten local ecology, people's lives and property.
no code implementations • 24 Jul 2023 • Menglin Kong, Ri Su, Shaojie Zhao, Muzhou Hou
In view of the model's differentiating ability for different task information flows, DEPHN uses feature explicit mapping and virtual gradient coefficient for expert gating during the training process, and adaptively adjusts the learning intensity of the gated unit by considering the difference of gating values and task correlation.
no code implementations • 24 Jul 2023 • Menglin Kong, Shaojie Zhao, Juan Cheng, Xingquan Li, Ri Su, Muzhou Hou, Cong Cao
There are two fundamental problems in applying deep learning/machine learning methods to disease classification tasks, one is the insufficient number and poor quality of training samples; another one is how to effectively fuse multiple source features and thus train robust classification models.
no code implementations • 20 May 2023 • Menglin Kong, Muzhou Hou, Shaojie Zhao, Feng Liu, Ri Su, Yinghao Chen
Click-Through Rate (CTR) prediction is one of the main tasks of the recommendation system, which is conducted by a user for different items to give the recommendation results.
no code implementations • 18 Jun 2022 • Ri Su, Alphonse Houssou Hounye, Cong Cao, Muzhou Hou
Based on the Sigmoid activation function of output layer, the linear addition activation value of parallel structures in the training process is easy to make the samples fall into the weak gradient interval, resulting in the phenomenon of weak gradient, and reducing the effectiveness of training.