Quality Assurance Team Leader
In this project, I led the data labeling efforts for a critical autonomous vehicle development initiative, focusing on creating high-quality annotated datasets to train machine learning models. The key elements of the project included: Scope: Annotated thousands of images captured from various driving environments, including urban streets, highways, and rural areas. The project involved detailed labeling of objects such as other vehicles, pedestrians, traffic signs, road markings, and environmental features. Objectives: To provide precise and reliable data for developing and refining object detection and recognition algorithms used in autonomous vehicles. Ensured that the labeled data accurately represented real-world scenarios to enhance the vehicle's ability to perceive and react to its surroundings. Tools and Techniques: Utilized advanced data labeling tools such as Labelbox for its robust annotation features and VGG Image Annotator for its flexibility. Implemented custom scripts