Vehicle classification approach based on the combined texture and shape features with a compressive DL

Author:

Sun Wei1ORCID,Zhang Xiaorui23,Shi Shunshun1,He Xiaozheng4

Affiliation:

1. School of AutomationNanjing University of Information Science & TechnologyNanjingPeople's Republic of China

2. School of Computer and SoftwareNanjing University of Information Science & TechnologyNanjingPeople's Republic of China

3. Jiangsu Collaborative Innovation Centre on Atmospheric Environment and Equipment TechnologyNanjingPeople's Republic of China

4. School of Computer and SoftwareDepartment of Civil and Environmental EngineeringRensselaer Polytechnic InstituteTroyNYUSA

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Publisher

Institution of Engineering and Technology (IET)

Subject

Law,Mechanical Engineering,General Environmental Science,Transportation

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1. Vehicle Detection in High Density Traffic Surveillance Data using YOLO.v5;Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering);2024-02

2. The Roll Stability Analysis of Semi-Trailer Based on the Wheel Force;Computers, Materials & Continua;2022

3. Energy-Efficient Internet of Things Solution for Traffic Monitoring;Energy-Efficient and Semi-automated Truck Platooning;2022

4. An Ensemble Broad Learning Scheme for Semisupervised Vehicle Type Classification;IEEE Transactions on Neural Networks and Learning Systems;2021-12

5. RSOD: Real-time small object detection algorithm in UAV-based traffic monitoring;Applied Intelligence;2021-10-29

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