(PCA), Convolutional Auto-Encoder (CAE), Self-Attention-based CAE (SA-CAE), Gate Recurrent Unit based Auto-Encoder (GRU-AE) and TFA-GRU-AE models; (2) flight patterns corresponding to different runways can be recognized; and (3) anomalous flights can effectively deviate from many ...
This is the official implementation ofAttention-based Residual Autoencoder for Video Anomaly Detection . Related works HSTforU: SeeHSTforU: Anomaly Detection in Aerial and Ground-based Videos with Hierarchical Spatio-Temporal Transformer for U-net. ...
This paper mainly studies methods based on voxel representation. The most commonly used 3D reconstruction model architecture is autoencoder structure such as [13]. However, when we reproduce the experiments of [13], [14], we find that the output models often lack detailed information on single-...
In this paper, we develop a hybrid deep learning-based fruit image classification framework, named attention-based densely connected convolutional networks with convolution autoencoder (CAE-ADN), which uses a convolution autoencoder to pre-train the images and uses an attention-based DenseNet to ...
Graph attention automatic encoder based on contrastive learning for domain recognition of spatial transcriptomics Article Open access 18 October 2024 Flexible integration of spatial and expression information for precise spot embedding via ZINB-based graph-enhanced autoencoder Article Open access 04 April...
L2g autoencoder: Understanding point clouds by local-to-global reconstruction with hierarchical self-attention (arXiv 2019)pdf Generative pretraining from pixels (PMLR 2020)pdf Exploring self-attention for image recognition (CVPR 2020)pdf Cf-sis: Semantic-instance segmentation of 3d point clouds by ...
Score function fff通常是两段文本q(表示query),p(表示passage)的点积,因为两个矩阵相乘是最简单直观的相似度度量。这就是最基本的attention机制的实现公式了。 f=qTpif = q^Tp_if=qTpi 基本attention公式变种 通过改变fff函数的计算方式,可以产生很多attention机制的变种,这些变种可能在某些特定的任务下比基本...
Anomaly detection and localization become necessary since humans are unable to spot visual frauds. Since it differs from the normal representation of shapes, colors, textures, size, and location, it does not have the potential to be employed in such practical applications. Hence, the automatic anom...
LSTM-autoencoder with attentions for multivariate time seriesThis repository contains an autoencoder for multivariate time series forecasting. It features two attention mechanisms described in A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction and was inspired by Seanny123's ...
【论文阅读|深读】RDAA:Role Discovery-Guided Network Embedding Based on Autoencoder and Attention Mechanism,IEEETransactionsonSystems,Man,andCybernetics:Systems代码:://github.com/cspjiao/RDAA年度:2021/06/29近年来,网络嵌入(networkembedding,NE)是复杂