Congratulations to Liu Yuhong on graduating successfully!

Liu Yuhong graduated from Anhui University of Traditional Chinese Medicine with a Bachelor’s degree. In September 2020, she began her master’s studies at the School of Computer Engineering and Science, Shanghai University. After joining the research group, she followed the guidance of Professor Han Yuexing to learn about material image processing and material image enhancement technologies and their applications. With the careful guidance of Professor Han, she completed the following research:

1. She proposed an image enhancement-based method for recognizing the morphology characteristics of thermal barrier coatings. The method consists of three steps: enhancement of pore contours and image denoising, pore removal and crack repair, and crack recognition and length calculation. It can successfully identify cracks in thermal barrier coatings. Additionally, the reasonable use of image filtering and mathematical morphology enhancement methods ensures high integrity and low deviation in crack recognition in thermal barrier coatings. The proposed method can automatically identify cracks in thermal barrier coatings and calculate their lengths. Compared to manual detection, this method provides more precise crack recognition and faster crack length calculation, providing effective assistance to material science researchers in analyzing the microstructure of thermal barrier coatings conveniently and efficiently.

2. She designed two software programs for identifying the morphology characteristics of thermal barrier coatings. One software program achieves thermal barrier coating image enhancement and crack skeleton extraction, while the other software program achieves crack recognition and length calculation. The combination of both software programs further improves the speed of analyzing the microstructure of thermal barrier coatings, reducing time and labor costs. Moreover, the software can also process other material images similar to thermal barrier coating images, promoting the research and development of material science.

3. She proposed a method for material image data augmentation using an improved HP-VAE-GAN. The improved HP-VAE-GAN uses a CBAM module to refine feature mapping and improve the network’s feature representation ability. Meanwhile, an additional convolutional block was added to the encoder network to further improve the network’s feature extraction ability and eliminate the impact of CBAM insertion on model performance. The generated results show that the proposed HP-VAE-GAN with the CBAM attention mechanism can effectively improve the quality of generated images. The results of classification experiments show that this method achieves better results than using HP-VAE-GAN for data augmentation, providing a new data augmentation approach for small sample material image datasets.

After graduating, Liu Yuhong became a teacher of Artificial Intelligence at Shanghai Zhenhua Vocational School. Throughout her three years of graduate studies at Shanghai University, Liu Yuhong worked hard to enhance her professional knowledge and research abilities. She had the privilege of meeting many excellent mentors and friends. We hope that Liu Yuhong will always remember her original aspirations and mission, overcome challenges, and forge ahead on her future path with determination.

Essay: Research on Enhancement Methods for Small Sample Material Images