Titlebook: Neural Computing for Advanced Applications; 5th International Co Haijun Zhang,Xianxian Li,Qian He Conference proceedings 2025 The Editor(s)

Gnrh670

Ziang Wang,Yifei Sun,Yifei Cao,Jie Yang,Wenya Shi,Ao Zhang,Jiale Ju,Jihui Yin,Qiaosen Yan,Xinqi Yangoffer specific biological and clinical information related to its action at both the GR and the MR. Therefore, the relevance of HPA axis dysfunction in psychiatric disorders and the ability to distinguish “true” from “pseudo-” treatment-resistant depression suggest that the PST holds an important clinical tool.

PLE

Tian Chen,Wenbin Chen,Huifei Gaooffer specific biological and clinical information related to its action at both the GR and the MR. Therefore, the relevance of HPA axis dysfunction in psychiatric disorders and the ability to distinguish “true” from “pseudo-” treatment-resistant depression suggest that the PST holds an important clinical tool.

斗爭

占卜者

吊胃口

水土

行乞

VEST

A New Indoor Occupancy Detection Model by Integrating the Efficient Multi-scale Attention Mechanism nd focus on human key information, this paper infuses the EMA mechanism with the EfficientDet model. Finally, a self-built classroom dataset has been constructed for validating the occupancy detection performance of the model. The experimental results show that the average recognition accuracy of th

笨重

A Novel Automatic Generation Method for?Neural Network by?Using Iterative Function Systemmance, encompassing the computation of the correlation coefficient between the output signal and the input signal, the variance and standard deviation of the output signal, as well as the reaction time. This study presents a novel approach for the automated development of neural network architecture

責(zé)怪

A Predictive Maintenance Platform for?a?Conveyor Motor Sensor System Using Recurrent Neural Networks other traditional regression machine learning models such as Extreme Gradient Boosting (XGboost). We compare the effectiveness of the PdM platform with two RNN models: a basic RNN model and a long short-term memory (LSTM) model. Unlike other regression PdM systems focusing on predicting devices Rem