At Samsung R&D, via Access Automation, I supported image-data projects from controlled capture and annotation through quality validation and final delivery. I delivered four projects with 30K–40K image datasets per project and a 100% acceptance rate.
I led and managed a team of 25 annotators, training the team to project requirements and assigning tasks. I also reviewed completed work and worked with R&D stakeholders to clarify specifications and acceptance criteria.
My project work included low-light and noise datasets, object annotation, and green-screen hair masking with alpha channels. I inspected framing, noise, sharpness, subject placement, and annotation accuracy against project requirements.
I used ATLAS Studio, CVAT, and Adobe Photoshop for annotation and visual QC, and wrote Python scripts and used CMD to segregate datasets and create QC and data-validation tools. My graphic design and UI/UX background informs my pixel-level visual judgment.
