Bounding Box Annotation
We enable an AI tool to detect objects through bounding boxes,
a fundamental of image annotation that comprises object
classification and localization. At Cenza, we use best of
tools and proven expertise to deliver fine-quality bounding box
annotation. Variance in box size, ensuring maximum tightness,
and minimizing box overlaps are our key priorities to
ensure complete precision.
We provide a wide range of image annotation services as a part AI/ML training,
thanks to our access to cutting-edge technologies, project-specific roadmaps,
and best-in-class industry practices. We can construct data sets that reflect
the context in which an AI/ML model will be employed to ensure successful
Cenza’s data experts handle all types of project complexities, from the typical
to the unexpected. We integrate techniques such as phrase recognition,
text categorization, semantic text annotation, and entity linking to
combine proportionate text tagging as well as labelling process.
Named Entity Recognition
A digital document contains several key parameters, and
for an AI/ML tool to classify them, it needs a special
technique – Named Entity Recognition (NER). For Legal AI
tools that will be dealing with documents comprising multiple
data points, our NER services will enable identification
of the named entities and classifying them under pre-defined
categories to help the machine understand the contextual meaning.