What is data annotation, and how is it used in machine learning?

Data Annotation is the process of identifying and classifying objects, elements or any other data present in images, texts, videos and audio. When we classify an object in an image or video, we add a label or metadata tag to that object. This process of labeling objects in any data form is called Data Annotation. Labelling helps the machine learning model to recognize the target objects which forms the basis for any computer vision oriented project to execute and process data and perform key tasks. To be precise, Data annotation helps the machine to recognize data in its correct form. Hence, it becomes an essential and important step in any machine learning model.

Machine learning generally requires huge amount of Trained Data which could be varied in terms of the target classes one is are trying to study. And when this trained data is fed into the algorithms as an input source for an AI system, the algorithm then correctly identifies, understand and consistently learn from it.

There are different types of data annotation methods available in which the annotations can be done but the aim of all these is to help machine recognize the texts, images, and videos (objects) in NLP or Computer Vision project.

Types of Data Annotations

Bounding Boxes: This is the most common and majorly used methods in which rectangular boxes are used to identify, tag and label the object.

Lines and Splines: The annotation is created by lines and splines to identify and recognize lanes. Primarily used to run an autonomous vehicle and autonomous terrain mapping

Semantic Segmentation: This is used where the environmental context is an important factor. Pixel-wise annotation is done in this method in which each pixel holds a semantic sense.

3D Cuboids: This method of annotation is similar to bounding boxes but provides extra information about the target object.

Polygonal Segmentation: This is used to identify complex polygons to find out the shape and location of the target object with accuracy.

Landmark and key-points: Dots are being used across the target object to identify the shape and other details. These type of annotations are more often used in detecting facial expressions, facial gestures, features or different poses

Entity Annotation: In this method, labeling of unstructured sentences is done so that the important information can be easily understood by a machine

Data Annotation Outsourcing Services | Data Labeling Companies — Anolytics is a company that provides these types of services with accuracy and quality. Apart from this, the company gives information and resources around the data annotation. Anolytics makes data labelling possible for almost every industry and sector to develop AI-based functional model work properly without any error. When it comes to the security of the data, Anolytics is certified with SOC 2 TYPE 1 Company for maintaining the high standards.

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