Is image annotation a hard AI problem? [closed]

Image Annotation is considered to be an AI-complete/AI-hard problem. This means that a homogenous machine can't solve it, and multiple levels within the problem make it complex.

1. What is the purpose of image annotation?
2. What is image annotation in deep learning?
3. How are image annotation useful for information systems?

What is the purpose of image annotation?

Image annotation is most commonly used to recognize objects and boundaries and to segment images for instance, meaning, or whole-image understanding. For each of these uses, it takes a significant amount of data to train, validate, and test a machine learning model to achieve the desired outcome.

What is image annotation in deep learning?

Image annotation is the process of labeling images in a given dataset to train machine learning models. When the manual annotation is completed, labeled images are processed by a machine learning or deep learning model to replicate the annotations without human supervision.

How are image annotation useful for information systems?

Image annotation is frequently used for image recognition, pose estimation, keypoint detection, image classification, object detection, object recognition, image segmentation, machine learning, and computer vision models.