Yi Wang

Advisor: Professor Emad Boctor and YiXuan Wu

Project1:Dual-robotic arm prostate ultrasound tomography

Project2: Motion tracking of a moving phantom based on convolutional neural network

Advisor: Professor Mehran Armand and David Usevitch and Adnan Munawar

Project: Virtual Reality Drilling Simulator for Laminectomy: Implementing and Evaluating Colored Guidance

• Learning and Data Mining Practical Training, Utilized data mining techniques to improve the accuracy of Myers-Briggs Type Indicator(MBTI) given by the post
• Performed data pre-processing and decision tree experiments, input the four categories under MBTI into the decision tree respectively, and enabled the accuracy rate to increase from 0.51 to 0.58
• Made a summary of the research results and completed a thesis.

• Participated in artificial intelligence research projects, responsible for optimizing relevant codes and models of the existing garbage classification functions to facilitate the realization of automatic garbage classification
• Collected codes, data sets and deep network models and selected the optimal model through data matching experiments
• Optimized the network model structure in three ways and further improved the accuracy of the model, with the adjusted experimental accuracy rate exceeding 80%
• Wrote a paper Design and Implementation of Garbage Classification System Based on Deep Learning (resnet model) as the first author and gained publication qualification on IEEE journals (Institute of Electrical and Electronics Engineers)
• Wrote a paper Garbage Classification System with YOLOV5 Based on Image Recognition as the fourth author, independently completed material collection and obtained the publication qualification at ICSIP 2021.