Prediction model of the end-point carbon content in BOF by constructing the graph of heats.ISIJ International,

dmPINNs: An Integrated Data-Driven and Mechanism-Based Method for Endpoint Carbon Prediction in BOF.Metals,2024,(14):

Defects detection in weld joints based on visual attention and deep learning.NDT & E,2023,(133):

Defect Detection for Wear Debris Based on Few-Shot Contrastive Learning.Applied sciences,2022,(12):

MFSR: Light Field Images Spatial Super Resolution Model Integrated with Multiple Features.Electronics,2023,(12):

Recognition of Plate Identification Numbers Using Convolution Neural Network and Character Distribution Rules.ISIJ International,2019,59(11):2044-2051.

Weld Defect Cascaded Detection Model Based on Bidirectional Multi-scale Feature Fusion and Shape Pre-classification.ISIJ International,2022,62(7):1485-1492.

Heat transfer performances of honeycomb regenerators with square or hexagon cell opening.Applied Thermal Engineering,2018,(125):790-798.

Prediction of endpoint phosphorus content of molten steel in BOF using weighted K-Means and GMDH neural network.Journal of Iron and Steel Research International,2012,19(1):11-16.

A two-step case-based reasoning method based on attributes reduction for predicting the endpoint phosphorus content.ISIJ International,2015,55(5):1035-1043.