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12/21/2022
Continual Interactive Behavior Learning With Traffic Divergence Measurement: A Dynamic Gradient Scenario Memory Approach
Developing autonomous vehicles (AVs) helps improve the road safety and t...
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11/18/2022
Leveraging Multi-stream Information Fusion for Trajectory Prediction in Low-illumination Scenarios: A Multi-channel Graph Convolutional Approach
Trajectory prediction is a fundamental problem and challenge for autonom...
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07/24/2022
Adaptive Decision Making at the Intersection for Autonomous Vehicles Based on Skill Discovery
In urban environments, the complex and uncertain intersection scenarios ...
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02/22/2022
An Ensemble Learning Framework for Vehicle Trajectory Prediction in Interactive Scenarios
Precisely modeling interactions and accurately predicting trajectories o...
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01/13/2022
Automatic Sparse Connectivity Learning for Neural Networks
Since sparse neural networks usually contain many zero weights, these un...
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11/11/2021
Driver-Specific Risk Recognition in Interactive Driving Scenarios using Graph Representation
This paper presents a driver-specific risk recognition framework for aut...
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11/06/2021
Prediction of Pedestrian Spatiotemporal Risk Levels for Intelligent Vehicles: A Data-driven Approach
In recent years, road safety has attracted significant attention from re...
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09/15/2021
Life-Long Multi-Task Learning of Adaptive Path Tracking Policy for Autonomous Vehicle
This paper proposes a life-long adaptive path tracking policy learning m...
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09/01/2021
Physics-informed Neural Network for Nonlinear Dynamics in Fiber Optics
A physics-informed neural network (PINN) that combines deep learning wit...
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03/05/2021
Data-Driven Short-Term Voltage Stability Assessment Based on Spatial-Temporal Graph Convolutional Network
Post-fault dynamics of short-term voltage stability (SVS) present spatia...
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07/11/2020
Driver Behavior Modelling at the Urban Intersection via Canonical Correlation Analysis
The urban intersection is a typically dynamic and complex scenario for i...
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05/19/2020
MOTS: Multiple Object Tracking for General Categories Based On Few-Shot Method
Most modern Multi-Object Tracking (MOT) systems typically apply REID-bas...
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11/25/2019
Co-contributorship Network and Division of Labor in Individual Scientific Collaborations
Collaborations are pervasive in current science. Collaborations have bee...
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09/24/2019
Bit-level Optimized Neural Network for Multi-antenna Channel Quantization
Quantized channel state information (CSI) plays a critical role in preco...
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07/27/2019
Analyzing Linguistic Complexity and Scientific Impact
The number of publications and the number of citations received have bec...
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02/04/2019
Dual Path Multi-Scale Fusion Networks with Attention for Crowd Counting
The task of crowd counting in varying density scenes is an extremely dif...
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11/19/2018
MIMO Channel Information Feedback Using Deep Recurrent Network
In a multiple-input multiple-output (MIMO) system, the availability of c...
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08/24/2018
An Enhanced SCMA Detector Enabled by Deep Neural Network
In this paper, we propose a learning approach for sparse code multiple a...
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07/22/2018
Examining Scientific Writing Styles from the Perspective of Linguistic Complexity
Publishing articles in high-impact English journals is difficult for sch...
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06/02/2018
Learning and Generalizing Motion Primitives from Driving Data for Path-Tracking Applications
Considering the driving habits which are learned from the naturalistic d...
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11/25/2017
