Image processing
I have also worked on image annotation tasks in the context of object detection, where I was involved in labeling visual data using bounding boxes and class annotations. This included identifying and marking objects within images, ensuring precise localization, and maintaining consistency across large datasets. I focused on accurate labeling of object boundaries, handling edge cases such as occlusions or overlapping objects, and verifying annotations to meet model training standards. This experience strengthened my attention to detail and ability to follow strict annotation guidelines. In addition, I contributed to validating and reviewing annotated datasets to ensure quality and consistency, which is critical for training reliable object detection models. I am familiar with common annotation formats (such as COCO and YOLO) and understand how labeling decisions impact model performance, including precision, recall, and generalization. My experience combines both annotation and quality control, allowing me to deliver high-quality labeled data suitable for training and evaluation of computer vision models.