Di Wu

Orcid: 0000-0003-1664-5893

Affiliations:
  • Northwestern Polytechnical University, Xi'an, Shaanxi, China
  • China University of Mining and Technology, School of Electrical and Power Engineering, Xuzhou, China
  • Changshu Institute of Technology, School of Electrical and Automatic Engineering, Suzhou, China


According to our database1, Di Wu authored at least 11 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
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Links

Online presence:

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Bibliography

2024
Isolated Random Forest Assisted Spatio-Temporal Ant Colony Evolutionary Algorithm for Cell Tracking in Time-Lapse Sequences.
IEEE J. Biomed. Health Informatics, July, 2024

A Survey of Deep Learning Based Radar and Vision Fusion for 3D Object Detection in Autonomous Driving.
CoRR, 2024

MonoDETRNext: Next-generation Accurate and Efficient Monocular 3D Object Detection Method.
CoRR, 2024

2023
A YOLO-GGCNN based grasping framework for mobile robots in unknown environments.
Expert Syst. Appl., September, 2023

MO-YOLO: End-to-End Multiple-Object Tracking Method with YOLO and MOTR.
CoRR, 2023

A Motion Status Discrimination Method Based on Velocity Estimation Embedded in Multi-object Tracking.
Proceedings of the 12th International Conference on Control, 2023

2021
A heuristic and reliable track-to-track data association approach for multi-cell track reconstruction.
Appl. Intell., 2021

A Cell Tracking Method with Deep Learning Mitosis Detection in Microscopy Images.
Proceedings of the Advances in Swarm Intelligence - 12th International Conference, 2021

A Mobile Robotic Arm Grasping System with Autonomous Navigation and Object Detection.
Proceedings of the 2021 International Conference on Control, 2021

2020
An Ant-Inspired Track-to-Track Recovery Approach for Construction of Cell Lineage Trees.
Proceedings of the Advances in Swarm Intelligence - 11th International Conference, 2020

2019
A real-time video surveillance and state detection approach for elevator cabs.
Proceedings of the 2019 International Conference on Control, 2019


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