Congratulations to Han Sifan on his successful graduation!
Han Sifan entered the School of Computer Engineering and Science at Shanghai University in September 2021, starting his master’s degree program. After joining the research group, he followed two teachers, Chen Qiaochuan and Han Yuexing, and focused on the research of deep learning based processing of material images to predict material properties. Under the guidance of two teachers, the following research content was completed:
-
Constructed a deep learning prediction material performance network based on global local feature extraction and multi feature fusion. This network adopts a dual branch multi-scale structural design, utilizing both global and local branch networks to extract global and local features from material microstructure images, without disrupting the modeling process of each feature. Integrating multi head self attention mechanism into the global branch network, dividing the feature map into multiple different subspaces, and mining the inherent correlation between features. Compared to existing methods, this network has successfully established a more complete and accurate “structure performance” mapping relationship.
-
In response to the problem of insufficient understanding of material microstructure images in complex scenes by current algorithms, which affects prediction accuracy, an efficient multimodal feature fusion network is proposed. This model includes a spectral feature extraction module, a local element feature extraction module, and a GLFS Net module for extracting material microstructure features. Through multi information fusion and the strategy of using material elements to assist in enhancing network details and material image microstructure, the network can ultimately achieve accurate prediction of material properties in complex scenes.
-
Applied for a patent for a method for predicting material properties. This patent is based on a lightweight network architecture, which comprehensively utilizes multimodal information combining images and text of materials, further improving the accuracy of material microstructure analysis and performance prediction.
After graduation, Han Sifan worked in the Zhuzhou Locomotive Research Institute of CRRC Zhuzhou Electric Locomotive Co., Ltd. to conduct research on autonomous driving. During my three years of graduate studies at Shanghai University, I worked hard to learn and also made many good teachers and friends. He has walked through many corners of Shanghai and will never forget it. He hopes to have the opportunity to meet everyone again in the future.
Essay: Research on Material Performance Prediction Based on Multi Feature Fusion
