Object Recognition is the task of identifying and classifying objects present in an image into predefined categories. It only outputs the class label for each object. For example, in the development of autonomous vehicles, traffic signs and lights can be recognized.
Object Detection goes a step further by not only recognizing the objects in an image but also locating their positions in the image by drawing a bounding box around each object. Thus, the same autonomous vehicles can benefit from detecting lane markings and pedestrians.
Image Segmentation is the task of dividing an image into multiple segments or regions, each corresponding to a different object or part of an object. It not only identifies objects but also separates the object from the background. The example is segmenting road, sky, and vehicles in driving scenes.
- Object Recognition classifies objects in an image.
- Object Detection locates and classifies objects in an image.
- Image Segmentation separates and classifies objects in an image.
Image recognition is a set of approaches to identify and analyze pictures in order to automate procedures like classification, tagging, detection, and segmentation.
Image classification is a process in AI where an algorithm is trained to identify and categorize objects or scenes in images.
Robotic Process Automation (RPA)
RPA is a software technology that enables building, deploying, and managing software robots that emulate human actions interacting with digital systems and software.