Bin Zhang l Semantic Segmentation for Autonomous Driving | Research Excellence Award

Assoc. Prof. Dr. Bin Zhang l Semantic Segmentation for Autonomous Driving | Research Excellence Award

Kanagawa University | Japan

Assoc. Prof. Dr. Bin Zhang is an associate professor and principal investigator specializing in intelligent machines, robotics, and AI-driven systems. Education includes a Ph.D. and M.S. in Mechanical and Intelligent Systems Engineering from The University of Electro-Communications and a B.S. in Automation. Professional experience spans academia and industry, with roles in mechanical engineering education and robotics research. Research interests focus on service robots, autonomous navigation, human–robot interaction, perception, deep learning, and assistive systems. Research skills include robot design, control, SLAM, computer vision, sensor fusion, and machine learning. Awards and honors recognize excellence in robotics, AI applications, and assistive technologies. Overall, Assoc. Prof. Dr. Bin Zhang contributes impactful research and education advancing intelligent robotic systems for society.

Citation Metrics (Scopus)

800
600
400
200
0

Citations
328

Documents
76

h-index
9

Citations

Documents

h-index


View Scopus Profile

Featured Publications

A Study on Improving the Accuracy of Semantic Segmentation for Autonomous Driving
Computers, Materials & Continua, 2026 · Open Access
A Quantitative Diagnosis Method for Assessing the Severity of Intake Filter Blockage of Heavy-Duty Gas Turbines Based on the Fusion of Physical Mechanisms and Deep Learning
Applied Thermal Engineering, 2025

A Performance Diagnosis Method for Full Gas-Path Components of Heavy-Duty Gas Turbines Based on Model- and Data-Hybrid Drive

Proceedings of the Chinese Society of Electrical Engineering, 2025

An End-to-End Pillar Feature-Based Neural Network Improved by Attention Modules for Object Detection of Autonomous Vehicles

IEEJ Transactions on Electrical and Electronic Engineering, 2025

2D Mapping Considering Potential Occupancy Space of Mobile Objects for a Guide Dog Robot

IEEJ Transactions on Electronics, Information and Systems, 2025

Daxiong Ji | Data Analysis | Research Excellence Award

Dr. Daxiong Ji | Data Analysis | Research Excellence Award

Zhejiang University | China

Dr. Daxiong Ji is an Associate Professor at the Institute of Marine Electronics and Intelligent Systems, Ocean College, Zhejiang University, and a Senior Member of IEEE. He earned his Ph.D. in Pattern Recognition and Intelligent Systems from the University of Chinese Academy of Sciences and a B.S. in Automation from Wuhan Polytechnic University. Dr. Ji has held visiting scholar positions at the University of Melbourne, University of Plymouth, and University of Victoria, collaborating internationally on advanced marine robotics research. His expertise spans automatic control, artificial intelligence applications, autonomous marine robotics, electrical engineering, and intelligent systems. He has supervised numerous undergraduate, master’s, and doctoral students, leading courses on Marine Robot Design, Marine Intelligent Systems, and Professional Practices. Dr. Ji has received multiple honors, including the First Prize of Zhejiang Provincial Teaching Achievement Award, recognition as an Excellent Moral Education Mentor, and awards for scientific and technological achievements from the Chinese Academy of Sciences. He has led and participated in numerous national and international research projects, focusing on autonomous navigation, fault diagnosis, and data-driven control of underwater vehicles. Dr. Ji is also an accomplished inventor with multiple patents in underwater robotics and autonomous systems. His research has been widely published in top journals, reflecting significant contributions to marine intelligent systems.

Profiles : Orcid | Google Scholar

Featured Publications

Ji, D.; Ogbonnaya, S.G.; Hussain, S.; Hussain, A.F.; Ye, Z.; Tang, Y.; Li, S. Three-Dimensional Dynamic Positioning Using a Novel Lyapunov-Based Model Predictive Control for Small Autonomous Surface/Underwater Vehicles. Electronics, 2025, 14(3), 489.

Xu, L.; Ji, D. Online Fault Diagnosis Using Bioinspired Spike Neural Network. IEEE Transactions on Industrial Informatics, 2024.

Zhou, J.; Ye, Z.; Zhao, J.; Ji, D.; Peng, Z.; Lu, G.; Tadda, M.A.; Shitu, A.; Zhu, S. Multi-detector and Motion Prediction-Based High-Speed Non-Intrusive Fingerling Counting Method. Biosystems Engineering, 2024, 218, 1–15.

Ji, D.; Wang, R. Path Following of QAUV Using Attitude-Velocity Coupling Model. Ocean Engineering, 2024, 293, 116885.

Ji, D.; Cheng, H.; Zhou, S.; Li, S. Dynamic Model-Based Integrated Navigation for a Small and Low-Cost Autonomous Surface/Underwater Vehicle. Ocean Engineering, 2023, 273, 114091.