The optimized 1DCNN-LSTM-Attention model outperforms other models, achieving an R2 value of 0.93. This work first validate the feasibility of utilizing advanced machine learning techniques for predicting energy consumption in UPM field, which can further promoting energy-efficient and sustainable UPM ...
原文:https://arxiv.org/abs/1910.03151 代码:https://github.com/BangguWu/ECANet 论文题目:ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks目录引言一、ECANet结构 二、ECANet代码三、将ECANet作为一个模块加 1Dcnn 神经网络 ...
特征融合:将CNN提取的特征向量和LSTM提取的特征向量进行融合,可以使用简单的连接操作将它们合并为一个更综合的特征向量。 全连接层和Softmax分类器:将融合的特征向量输入到全连接层中,该层可以学习到特征之间的非线性关系。最后,通过Softmax分类器进行分类,将特征映射到不同的类别。 这个流程结合了GASF矩阵、CNN、LST...
Feng L, Cheng C, Zhao M, Deng H, Zhang Y (2022) EEG-based emotion recognition using spatial-temporal graph convolutional lSTM with attention mechanism. IEEE J Biomed Health Inf 26(11):5406–5417. https://doi.org/10.1109/JBHI.2022.3198688 Article MATH Google Scholar Liu B, Guo J, Chen...
Self-Attention-Based Deep Convolution LSTM Framework for Sensor-Based Badminton Activity Recognition Sensor-based human activity recognition aims to classify human activities or behaviors according to the data from wearable or embedded sensors, leading to ... J Deng,S Zhang,J Ma - 《Sensors》 被引...
提出了一种面向频谱特征识别的深度学习算法,即Multi-level attention CNN Bi-LSTM(MCBL).MCBL有效融合了卷积神经网络,循环神经网络(Recurrent Neural Network,RNN)... 段强 - 《国防科技大学》 被引量: 0发表: 2021年 基于深度学习的雷达辐射源识别技术研究 3.提出了一种基于优化CNN的雷达辐射源识别方法,给出...
Therefore, The LSTM was improved with weight amplification [16] and macroscopic-microscopic attention [17] by Qin et al. The improved model was used for the life monitoring of bearings and its validity was proved through experiments. For the vibration signal of bearings is a natural time series...
关键词：故障诊断；自注意力机制；卷积神经网络；双向长短期记忆网络；机械装备 中图分类号：TP183 文献标识码：A 文章编号：1003-9767（2021）23-080-04 1DCNN-BiLSTM Model with Self-Attention Mechanism and its Application in Fault Diagnosis of Rolling Bearings LIU Xinzhi 1*, PENG Cheng 1, ...
原文:https://arxiv.org/abs/1910.03151 代码:https://github.com/BangguWu/ECANet 论文题目:ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks目录引言一、ECANet结构 二、ECANet代码三、将ECANet作为一个模块加 1Dcnn 神经网络 ...
原文:https://arxiv.org/abs/1910.03151 代码:https://github.com/BangguWu/ECANet 论文题目:ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks目录引言一、ECANet结构 二、ECANet代码三、将ECANet作为一个模块加 1Dcnn 神经网络 keras tensorflow cnn 转载 epeppanda 2024-02-19 ...