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A method for short-term passenger flow prediction in urban rail transit based on deep learning
Short-term passenger flow prediction is a critical component of urban rail transit operations. However, predictions of passenger flow are mostly...
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A Novel Method Based on Gunnar Farneback Method, Mathematical Morphology, and Artificial Vision for Flow Analysis in Electrochemical Reactors
Parallel flat plate electrochemical reactors are versatile devices that are used in a wide range of applications, including hydrogen production,...
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Traffic flow prediction based on graph convolutional networks with a parallel attention network and stacked gate recurrent units
Accurate traffic flow prediction is essential to address traffic issues and assist traffic managers make informed decisions in intelligent...
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A real-time two-stage and dual-check template matching algorithm based on normalized cross-correlation for industrial vision positioning
In this paper, a fast template matching algorithm of two-stage and dual-check bounded partial correlation (TDBPC) based on normalized...
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GelFlow: Self-supervised Learning of Optical Flow for Vision-Based Tactile Sensor Displacement Measurement
High-resolution multi-modality information acquired by vision-based tactile sensors can support more dexterous manipulations for robot fingers....
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Detecting Heel Strikes for Gait Analysis Through Higher-Order Motion Flow
In gait analysis, heel strikes are an important and preliminary cue because gait period, step and stride length can be derived accurately by the...
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Flow analysis-based fast-moving flow calibration for a people-counting system
We propose a new vision-based people-counting method that uses flow analysis with the movement speed of a person to increase the accuracy of...
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Generalized Gradient Flow Based Saliency for Pruning Deep Convolutional Neural Networks
Model filter pruning has shown efficiency in compressing deep convolutional neural networks by removing unimportant filters without sacrificing the...
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Traffic Flow Prediction with Swiss Open Data: A Deep Learning Approach
Open government data (OGD) are provided by the public sector and governments in an open, freely accessible format. Among various types of OGD,...
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Data-assisted training of a physics-informed neural network to predict the separated Reynolds-averaged turbulent flow field around an airfoil under variable angles of attack
Physics-informed neural networks are a promising method to yield surrogate models of flow fields. We present a metamodeling technique for variable...
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Traffic flow prediction using support vector regression
Traffic flow prediction is a crucial measure in Intelligent Transportation System. It helps in efficiently handling the future vehicular load on the...
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Multi-feature fusion prediction of fatigue driving based on improved optical flow algorithm
To predict whether a driver is fatigued, a fatigue prediction algorithm based on the fusion of improved optical flow features and microfeatures was...
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The Right Spin: Learning Object Motion from Rotation-Compensated Flow Fields
A good understanding of geometrical concepts as well as a broad familiarity with objects lead to excellent human perception of moving objects. The...
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Transformer network with decoupled spatial–temporal embedding for traffic flow forecasting
Over the past few years, there has been significant research on applying Transformer models to time series prediction, yielding promising results....
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Element-free Galerkin analysis of MHD duct flow problems at arbitrary and high Hartmann numbers
A stabilized element-free Galerkin (EFG) method is proposed in this paper for numerical analysis of the generalized steady MHD duct flow problems at...
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Attention-based spatial–temporal adaptive dual-graph convolutional network for traffic flow forecasting
Accurate traffic flow forecasting (TFF) is a prerequisite for urban traffic control and guidance, which has become the key to avoiding traffic...
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Real-time prediction of gas flow dynamics in diesel engines using a deep neural operator framework
The objective of this work is to address the need for fast and accurate models for analyzing transient gas flow dynamics in diesel engines. We employ...
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Micro-expression Recognition Based on Local Optical Flow Capsule Network
Micro-expression (ME) is a kind of facial muscle movement spontaneously, which can reflect people’s real emotions and be widely used in psychological...
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Hypergraph p-Laplacians, Scale Spaces, and Information Flow in Networks
The aim of this paper is to revisit the definition of differential operators on hypergraphs, which are a natural extension of graphs in systems based...
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Multi-perspective convolutional neural networks for citywide crowd flow prediction
Crowd flow prediction is an important problem of urban computing with many applications, such as public security. Inspired by the success of deep...
