Image Annotations & Labeling in 2022, THE ULTIMATE GUIDE!

[Music] the robustness of artificial intelligence capabilities in any technology depends on the training the ai and ml algorithms and the technology have received to train such algorithms large amounts of data sets are needed but such data sets in the raw form cannot be interpreted by these ai and ml algorithms hence raw data sets need to be converted into meaningful information that the ai algorithms can understand a process known as computer vision the process of data annotation accurately identifies or labels objects in the raw data sets and prepares the data for the training of the ai and ml algorithms one of the most important annotation processes includes image annotation and labeling various objects and image data sets are accurately labeled and annotated to prepare the data set for the training of ai algorithm let's look at some industries in which image annotations are widely used retail companies are increasingly adopting ai-based solutions to understand and store customer preferences footfall analysis in shopping malls data-driven product categorization and restocking for cars like tesla self-driving capabilities and 8-ask features of vehicles require precisely annotated image data sets to identify objects such as trees and people improved lane detection and improve overall safety in the healthcare industry autonomous robot surgery digital pathology and x-rays require a large number of accurately labeled and annotated medical image data sets to develop extremely safe ai algorithms robotic automation such as boston dynamics robot dog and amazon warehouse machines require high volumes of annotated image data sets to train the ai algorithms for a variety of real-life situations and mimic human in general computer vision using data annotation has resulted in higher efficiency improved quality control and increased safety across many industries at annotation labs our subject matter experts closely analyze your business problem and industry needs to cure it and provide you with the best annotation and labeling solutions there are several tools for image annotations 2d bounding boxes are rectangular boxes drawn as boundaries around objects and images while 3d bounding boxes add the elements of height width and depth to the rectangular boxes improving accuracy polygonal labeling is best used for irregular asymmetrical and blurred objects and images semantic segmentation annotates each and every pixel of the objects in the images and therefore improves the accuracy keypoint labeling tracks movement and facial expressions in the images polyline annotation determines the physical boundaries for the ai technology to work within such as lane detection for self-driving cars annotating three d point clouds of lidars can achieve an accuracy of up to one centimeter making it useful for navigation and determining the range and direction of movement usually one or more different types of image annotations are used for higher accuracy of image training data sets we achieve 95 plus accuracy in our annotations of image data sets for advanced training of your ai and ml algorithms speak with our experts today at annotationlabs.com [Music]

Channel: Annotation Labs

Views: 3,041

Keywords: Data annotation, data labeling, image annotation, image labeling, machine learning, artificial intelligence, image datasets, annotationlabs

Id: R1VtLluDoZI

Length: 3min 42sec (222 seconds)

Published: Mon Jul 25 2022