Multimodal Image Annotation and Language Validation for AI Training Data
Performed high accuracy data labeling and validation of multimodal AI training data that used image and textual inputs. Applied bounding boxes, polygon annotations and semantic segmentation and keypoint labeling to assist object detection and classification models. Edited and approved annotation results to make sure that visual data and related textual answers are matched. Ascertained and confirmed text in images with high regard to grammatical correctness, readability and completeness. Conducted quality assurance activities such as error identification, relabeling and testing of dataset consistency. Replied the answers in understandable and independent answers without references to the visual context and recorded the cases of ambiguity or an unanswerable question. Regularly achieved productivity and quality standards in remote annotation processes and worked within the project specifications.