iMerit’s CV experts use rectangular box annotation to illustrate objects and train data, enabling algorithms to identify and localize objects during the ML processes.
Expert annotators plot points on each vertex of the target object within an image. Polygon annotation allows all of the object’s exact edges to be annotated, regardless of shape.
An image can be segmented into component objects, by the iMerit team, and annotated. iMerit CV experts detect desired objects within an image at the pixel level.
iMerit teams outline objects and shape variations by connecting individual points across images. This annotation type detects body features, and could include facial expressions and emotions.
Audio & Handwriting Transcription
iMerit language experts transcribe text documents and audio clips including domain-specific material, such as earnings calls in the financial services sector and doctor prescriptions for medical AI.
Named Entity Recognition
iMerit provides the human nuance data scientists need by extracting and classifying relevant named entities in varieties of text sources. iMerit’s custom tooling streamlines this extraction process.
Domain experts review vast numbers of documents and provide sentiment judgments using three-way classification: positive, negative and neutral. Jobs often include intensity of sentiment.
Identifying the most relevant elements of a text can make a difference in triggering the appropriate response. iMerit teams subjectively rate salience of entities with single or multiple judgments.