We propose a deep-learning architecture combined residual network (ResNet), graph convolutional network (GCN) and long short-term memory (LSTM) (called “ResLSTM”) to forecast short-term passenger flow in urban rail transit on a network scale. First, improved methodologies of ResNet, GCN, an...
The authors first used a graph convolutional network (GCN) to learn the nodes’ representations in the graph for NER. The strategy used the syntactic relationships between words in a sentence to enhance NER performance. The CDR Dataset was used to evaluate the model's performance, and the ...
Python轴承故障诊断 (五)基于EMD-LSTM的故障分类 建模先锋 444 0 时频图像/多模态+顶会论文创新,故障诊断发文不是梦! 建模先锋 37 0 超强!一区直接写!基于SSA+Informer-SENet故障诊断模型 建模先锋 48 0 图卷积故障诊断,新增GAT、SGCN、GIN分类模型 建模先锋 39 0 Python轴承故障诊断 (13)基于故障信号...
从入门到进阶,一口气讲透CNN、RNN、GAN、GNN、DQN、Transformer、LSTM等八大深度学习神经网络算法!真的不要太爽! 1268 1 01:16:53 App Keras 搭建迁移学习平台(分类、语义分割、目标检测) 1141 18 07:18:45 App 不愧是公认最好的【图神经网络GNN/GCN教程】,迪哥2小时带你系统解读从基础到进阶再到实战!(...
A clinically named entity recognition model using deep neural networks and pre-trained word embeddings was created by Dash et al. [21]. To obtain an amazing F1-Score of 88.34%, the model uses a Bidirectional-Long Short-Term Memory (Bi-LSTM) network with a Conditional Random Field (CRF), ...
涨点创新 | 基于 Informer-LSTM的并行预测模型 建模先锋 271 0 图卷积故障诊断,新增GAT、SGCN、GIN分类模型 建模先锋 36 0 超强!一区直接写!基于SSA+Informer-SENet故障诊断模型 建模先锋 44 0 独家创新 | KAN、KAN卷积结合注意力机制! 建模先锋 39 0 1DCNN-2DResNet并行故障诊断模型 建模先锋 74 0 ...
Room-level fall detection based on ultra-wideband (UWB) monostatic radar and convolutional long short-term memory (LSTM). Sensors 2020, 20, 1105. [Google Scholar] [CrossRef] [PubMed] Yadav, S.K.; Tiwari, K.; Pandey, H.M.; Akbar, S.A. A review of multimodal human activity ...