Dataset Annotation and Segmentation for Road Extraction Project
Performed manual annotation correction and segment label revision on high-resolution road extraction datasets for a semantic segmentation project. Created and refined training, validation, and test dataset splits and implemented preprocessing routines in Python. Supported machine learning workflow for benchmarking algorithms and improving model accuracy. • Annotated and corrected road labels on satellite images using segmentation tools • Processed geospatial data, normalized images, and managed label consistency • Utilized Python-based internal tools for data labeling and split management • Improved local dataset quality with two rounds of systematic annotation revision.