Congratulations to Wei Huishan on successfully graduating!

Wei Huishan, who graduated with a bachelor’s degree from Anhui University of Science and Technology, joined the School of Computer Engineering and Science at Shanghai University in 2019 to pursue a research-oriented master’s degree. Under the guidance of Professor Han Yuexing, her main research focus is material image segmentation. Over the course of three years under Professor Han’s supervision, she has accomplished the following research projects:

1. We proposed a material image segmentation method based on graph convolution and deep learning to address the challenges of small sample sizes and complex textures in material images. This method incorporates residual connections and multi-scale fusion modules to enrich the information in feature maps. It also utilizes a dual attention mechanism based on graph convolution to enhance the focus on crucial features. Additionally, convolution layers in the deconvolutional part are added to improve the network’s non-linear expressive power.

2. To address the issue of feature loss when using excessive convolutional layers on small sample datasets, we designed a graph attention module based on skip connections using UNet as the backbone network. This method combines the ideas of convolutional neural networks and connects graph convolution and graph attention layers. It aims to fuse multi-dimensional node features from a graph structure perspective. By deepening the network while reducing the loss of pixel-level and spatial information, the goal is to improve the segmentation performance of the network.

3. We implemented the cross-domain application of graph convolution techniques in semantic segmentation tasks. We proposed a graph encoder and graph decoder that transform feature maps into a graph structure. This transformation allows the feature maps generated during the convolution process to be converted into a graph structure with a corresponding number of nodes. This approach facilitates the application of graph convolutional neural networks in semantic segmentation tasks.

After graduating, Wei Huishan joined the ZeroBeam Software Branch of SAIC Group. The three years of graduate studies have broadened her horizons and exposed her to the fascinating field of computer vision. She has witnessed the extensive applications of deep learning, especially in image processing, and has had the opportunity to meet many inspiring mentors and friends. Wei Huishan aspires to continue progressing and making the most of her journey in the future.

Essay: Research on Material Image Segmentation based on Graph Convolutional Neural Networks