Deep Attention
37 papers with code • 0 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Deep Attention
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METU-VIREF Dataset
Latest papers with no code
Uncertainty-Aware Deep Attention Recurrent Neural Network for Heterogeneous Time Series Imputation
We propose DEep Attention Recurrent Imputation (DEARI), which jointly estimates missing values and their associated uncertainty in heterogeneous multivariate time series.
Incorporating Riemannian Geometric Features for Learning Coefficient of Pressure Distributions on Airplane Wings
The aerodynamic coefficients of aircrafts are significantly impacted by its geometry, especially when the angle of attack (AoA) is large.
The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit
Motivated by the success of Transformers, we study the covariance matrix of a modified Softmax-based attention model with skip connections in the proportional limit of infinite-depth-and-width.
Between-Sample Relationship in Learning Tabular Data Using Graph and Attention Networks
We investigate our hypothesis using several GNNs and state-of-the-art (SOTA) deep attention models to learn the between-sample relationship on ten tabular data sets by comparing them to traditional machine learning methods.
Sparsity and Coefficient Permutation Based Two-Domain AMP for Image Block Compressed Sensing
In this paper, to overcome the issues and develop a high-performance LDAMP method for image block compressed sensing (BCS), we propose a novel sparsity and coefficient permutation-based AMP (SCP-AMP) method consisting of the block-based sampling and the two-domain reconstruction modules.
Speaker Diaphragm Excursion Prediction: deep attention and online adaptation
Speaker protection algorithm is to leverage the playback signal properties to prevent over excursion while maintaining maximum loudness, especially for the mobile phone with tiny loudspeakers.
Deep Attention Unet: A Network Model with Global Feature Perception Ability
Remote sensing image segmentation is a specific task of remote sensing image interpretation.
Deep Attention Network for Enhanced Hand Gesture Recognition System
Available datasets were collected to train the deep neural network architecture to create a gesture recognition system.
Relate auditory speech to EEG by shallow-deep attention-based network
Electroencephalography (EEG) plays a vital role in detecting how brain responses to different stimulus.
LocalEyenet: Deep Attention framework for Localization of Eyes
The model architecture, build on stacked hourglass backbone, learns the self-attention in feature maps which aids in preserving global as well as local spatial dependencies in face image.
