Bin Li

Orcid: 0000-0002-0197-3248

Affiliations:
  • Huazhong University of Science and Technology, State Key Laboratory of Digital Manufacturing Equipment and Technology, Wuhan, China
  • Huazhong University of Science and Technology, School of Mechanical Science and Engineering, Wuhan, China (PhD 2006)


According to our database1, Bin Li authored at least 24 papers between 2008 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Online presence:

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Bibliography

2024
A-Net: An A-Shape Lightweight Neural Network for Real-Time Surface Defect Segmentation.
IEEE Trans. Instrum. Meas., 2024

2023
A generalized well neural network for surface defect segmentation in Optical Communication Devices via Template-Testing comparison.
Comput. Ind., October, 2023

A novel deep learning method with partly explainable: Intelligent milling tool wear prediction model based on transformer informed physics.
Adv. Eng. Informatics, August, 2023

A transformed-feature-space data augmentation method for defect segmentation.
Comput. Ind., May, 2023

Selecting informative data for defect segmentation from imbalanced datasets via active learning.
Adv. Eng. Informatics, April, 2023

2022
Region- and Strength-Controllable GAN for Defect Generation and Segmentation in Industrial Images.
IEEE Trans. Ind. Informatics, 2022

Joint-Prior-Based Uneven Illumination Image Enhancement for Surface Defect Detection.
Symmetry, 2022

Defect attention template generation cycleGAN for weakly supervised surface defect segmentation.
Pattern Recognit., 2022

2020
Tool Wear Prediction via Multidimensional Stacked Sparse Autoencoders With Feature Fusion.
IEEE Trans. Ind. Informatics, 2020

Defect Image Sample Generation With GAN for Improving Defect Recognition.
IEEE Trans Autom. Sci. Eng., 2020

Uneven Illumination Surface Defects Inspection Based on Saliency Detection and Intrinsic Image Decomposition.
IEEE Access, 2020

2019
Using Multiple-Feature-Spaces-Based Deep Learning for Tool Condition Monitoring in Ultraprecision Manufacturing.
IEEE Trans. Ind. Electron., 2019

Early Fault Detection of Machine Tools Based on Deep Learning and Dynamic Identification.
IEEE Trans. Ind. Electron., 2019

Design of deep learning accelerated algorithm for online recognition of industrial products defects.
Neural Comput. Appl., 2019

Automated defect inspection of LED chip using deep convolutional neural network.
J. Intell. Manuf., 2019

DefectGAN: Weakly-Supervised Defect Detection using Generative Adversarial Network.
Proceedings of the 15th IEEE International Conference on Automation Science and Engineering, 2019

2016
Influence of information overload on operator's user experience of human-machine interface in LED manufacturing systems.
Cogn. Technol. Work., 2016

EID vs UCD: A Comparative Study on User Interface Design in Complex Electronics Manufacturing Systems.
Proceedings of the Engineering Psychology and Cognitive Ergonomics, 2016

2015
Skeuomorphism and Flat Design: Evaluating Users' Emotion Experience in Car Navigation Interface Design.
Proceedings of the Design, User Experience, and Usability: Design Discourse, 2015

2014
Experimental Study on Cutter Deflection in Multi-axis NC Machining.
Proceedings of the Intelligent Robotics and Applications - 7th International Conference, 2014

2013
A Complete Methodology for Estimating Dynamics of the Heavy Machine Tool Structure.
Proceedings of the Intelligent Robotics and Applications - 6th International Conference, 2013

2008
Adaptive Notch Filter Control for the Torsion Vibration in Lead-Screw Feed Drive System Based on Neural Network.
Proceedings of the Intelligent Robotics and Applications, First International Conference, 2008

A Method of General Stiffness Modeling for Multi-axis Machine Tool.
Proceedings of the Intelligent Robotics and Applications, First International Conference, 2008

Look-Ahead Scheme for High Speed Consecutive Micro Line Interpolation Based on Dynamics of Machine Tool.
Proceedings of the Intelligent Robotics and Applications, First International Conference, 2008


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