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SSTA-Net: Self-supervised Spatio-Temporal Attention Network for Action Recognition
Action recognition aims to identify the action categories and features in the video by analyzing the actions and behavior patterns that are...
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Local-aware spatio-temporal attention network with multi-stage feature fusion for human action recognition
In the study of human action recognition, two-stream networks have made excellent progress recently. However, there remain challenges in...
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A novel framework for fine-grained spatio-temporal change detection in satellite images
Change Detection(CD), in the context of remote sensing, determines the differences in different portions of land images when studied over a while....
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Motor Imagery Classification Based on CNN-GRU Network with Spatio-Temporal Feature Representation
Recently, various deep neural networks have been applied to classify electroencephalogram (EEG) signal. EEG is a brain signal that can be acquired in...
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A Fuzzy Error Based Fine-Tune Method for Spatio-Temporal Recognition Model
The spatio-temporal convolution model is widely recognized for its effectiveness in predicting action in various fields. This model typically uses...
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Granger causality-based cluster sequence mining for spatio-temporal causal relation mining
We proposed a method to extract causal relations of spatial clusters from multi-dimensional event sequence data, also known as a spatio-temporal...
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STRAN: Student expression recognition based on spatio-temporal residual attention network in classroom teaching videos
In order to obtain the state of students’ listening in class objectively and accurately, we can obtain students’ emotions through their expressions...
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Deep-Eware: spatio-temporal social event detection using a hybrid learning model
Event detection from social media aims at extracting specific or generic unusual happenings, such as, family reunions, earthquakes, and disease...
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Spatio-Temporal Context Modeling for Road Obstacle Detection
Road obstacle detection is an important problem for vehicle driving safety. In this paper, we aim to obtain robust road obstacle detection based on...
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Construction of a thinking model for Literary Writing based on Deep Spatio-Temporal Residual Convolutional Neural Networks
A system's capacity to distinguish between human-written input and Literary Writing (LW) is known as LW. LW entered by scanning is considered...
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Efficient Multi-object Detection for Complexity Spatio-Temporal Scenes
Multi-Object detection in traffic scenarios plays a crucial role in ensuring the safety of people and property, as well as facilitating the smooth...
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Convolutional neural network with spatio-temporal-channel attention for remote heart rate estimation
Remote photoplethysmography (rPPG), which measures human heart rate without physical contact with the skin, has become active research in recent...
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T-DANTE: Detecting Group Behaviour in Spatio-Temporal Trajectories Using Context Information
The present study addresses the group detection problem using spatio-temporal data. This study relies on modeling contextual information embedded in...
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STLGRU: Spatio-Temporal Lightweight Graph GRU for Traffic Flow Prediction
Reliable forecasting of traffic flow requires efficient modeling of traffic data. Indeed, different correlations and influences arise in a dynamic...
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Person Reidentification using 3D inception based Spatio-temporal features learning, attribute recognition, and Reranking
Identifying pedestrians in video sequences captured by non-overlap** multi-cameras is referred to as video-based Person Re-identification. The...
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Illu-NASNet: unsupervised illumination estimation based on dense spatio-temporal smoothness
Illumination estimation is a highly challenging problem. Many methods are learning from multi-image by unsupervised learning. However, these methods...
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Fall detection method based on Spatio-temporal feature fusion using combined two-channel classification
Nowadays, the growing population of senior citizens is a challenge for almost all develo** countries. New technologies can help monitor elderlies...
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Efficient Spatio-Temporal Graph Neural Networks for Traffic Forecasting
Urban Traffic Forecasting has recently seen a lot of research activity as it entails a compelling combination of multivariate temporal data with...
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Towards robust trajectory similarity computation: Representation-based spatio-temporal similarity quantification
Quantifying the trajectory similarity is a fundamental functionality in analysis tasks of spatio-temporal data. Existing classic methods compute the...
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Pyramidal Signed Distance Learning for Spatio-Temporal Human Shape Completion
We address the problem of completing partial human shape observations as obtained with a depth camera. Existing methods that solve this problem can...