Shenghan Guo
Faculty, Arizona State University
Fall 2024
Shubham Chetan Shah
Software engineering
Improving YOLOv8 Transferability via Model Fine-Tuning with Domain-Specific Manufacturing Data
Fine-tuning YOLOv8 with manufacturing data improves crack detection, boosting model transferability across diverse industrial applications.
Program: MORE
Summer 2024
Ethan Chang
Computer systems engineering
Optimizing Motion Paths in Physical Work: Integrating Task-Related and Environmental Constraints
Optimizing motion paths of physical work will simultaneously enhance worker productivity and safety while reducing task development costs.
Program: FURI
Spring 2024
Thinh Tran
Computer science
Optimizing Camera Locations for Efficient Human Motion Analysis
Optimizing camera locations for human motion analysis enhances workplace safety through better understanding of motion patterns.
Program: FURI
Ethan Chang
Computer systems engineering
Sensor Fusion System for Improving Motion Amount Quantification within Computer-Vision-Enabled Worker Analysis
Developing a sensor fusion system for computer vision models will both increase the accuracy and reduce the costs of motion data analysis.
Program: FURI
Neel Hasmukhbhai Macwan
Robotics and autonomous systems
Computer-Vision-Enabled Video Analysis for Motion Amount Quantification
Developing a novel approach for quantifying motion amounts in in-situ videos, with a focus on the local and collective motion of a specific joint.
Program: MORE
Spring 2023
Srinidhi Budhiraju
Computer science
Multi-Conditional cGAN Model for Resistance Spot Welding Dataset
Improving the resistance spot welding process will lead to advances in the automobile and aeronautical industries.
Program: FURI