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Image Annotation Techniques

Training intelligent machines with algorithms require precise datasets that are processed using different annotation techniques. Being an image labeling expert, we have immense experience and expertise in various types of data annotation services. Types of annotation that we do are listed below.

Annotation Techniques

Training intelligent machines with algorithms require precise datasets that are processed using different annotation techniques. Being an image labeling expert, we have immense experience and expertise in various types of data annotation services. Types of annotation that we do are listed below.

2D Bounding Box Annotation

A perfectly bounding 2D box is used to label the objects in a given 2D image. Mostly used in creating datasets for autonomous vehicle training.

Polygon/Contour Annotation

Objects in an image are labeled by drawing an accurate contour around it. Used in creating datasets for training precise application models.

Semantic Segmentation

The image is segmented semantically at its pixel level. Based on the pixel labeling, semantic segmentation is of 2 types:

  • Full pixel/Standard segmentation
  • Instance segmentation.

Cuboidal Annotation

Labeling of objects in an image using cuboids for processing 3D training data. This technique can be used in both 2D images and 3D point cloud data.

Key Point Annotation

Objects in an image are labeled using points to determine the shape of it. Key point annotation are used to label facial/skeletal features, automotive parts etc.

Polyline Annotation

It is the labeling of lanes using splines. Exclusively used for validating ADAS systems in autonomous vehicle training.