To solve these challenges, this paper proposes a novel robust detector named HTA-CTD, incorporating the Hierarchical Temporal Attention (HTA) and Competent Teacher Network (CTN). HTA introduces an adaptive temporal-frequency feature extraction method, while CTN minimizes reliance on strong labels. ...
Temporal self-attentionNetwork embedding aims to learn low-dimensional representations of nodes while capturing structure information of networks. It has achieved great success on many tasks of network analysis such as link prediction and node classification. Most of existing network embedding algorithms ...
Besides, the inherent temporal dynamics of exogenous data are also related to the target series prediction, and thus should be considered as well. To address these issues, we propose an end-to-end deep learning model, i.e., Hierarchical attention-based Recurrent Highway Network (HRHN), which...
HEANet: Hierarchical-Feature Enhanced Attention Network for Remote Sensing Change Detection 来自 Springer 喜欢 0 阅读量: 12 作者:F Mu,Y Pan,J Li,H Qin,N Shen,X Xu,Z Chen,T Xu 摘要: Change detection enables the detection of changes in objects from multi-temporal images. Recently, deep ...
2.2 Temporal Attentive RNN for Evolutionary Patterns 时序演化模式展示了节点和边随时间推移而出现或消失的情况。DyHATR中的分层注意力模型可以有效捕捉到静态快照网络中的异质信息。但是无法建模随时间的演化模式。最近,用于动态网络嵌入方法的循环神经网络 (RNN) 的引入取得了可喜的性能 [11,29,35,27]。在我们的...
We propose a hierarchical transformer encoder that incorporates multi-scale spatio-temporal attention. We use multi-scale feature maps, i.e., leverage all layers’ attention maps, and improve performance on benchmarks that provide sparse supervision. ...
The temporal requirements of an associative memory model deserve attention from both the technical and biophysical perspectives, partly determining the model’s efficiency. From a purely algorithmic point of view, the pattern recognition community is currently facing the challenge of solving as quickly ...
In this paper, we propose a novel IDS called the hierarchical spatial-temporal features-based intrusion detection system (HAST-IDS), which first learns the low-level spatial features of network traffic using deep convolutional neural networks (CNNs) and then learns high-level temporal features ...
【12】Hierarchical Temporal Attention Network for Thyroid Nodule Recognition Using MICS_China 878 -- 3:38 Demo of "Learning Hierarchical Cross-Modal Association for Co-Speech Gesture Gen 人工智能基地2 100 -- 16:35 【论文阅读】Learning Hierarchical Cross-Modal Association for Co-Speech Gesture Ge...
Real-world timeseries have complex underlying temporal dynamics and the detection of anomalies is challenging. In this paper, we propose the Temporal Hierarchical One-Class (THOC) network, a temporal one-class classification model for timeseries anomaly detection. It captures temporal dynamics in mult...