As points of reference for object detection, bounding boxes are drawn over images by data annotators, outlining objects of interest with well-defined coordinates within each image.
It is supervised deep learning algorithms that work behind autonomous driving. The computer vision system of all self-driving vehicles has to be trained and tuned with a large amount of structured, annotated & labeled data. We at Anolytics specialize in developing high-quality, error-free, human-labeled, and cost-effective AI training data for autonomous vehicles.
As points of reference for object detection, bounding boxes are drawn over images by data annotators, outlining objects of interest with well-defined coordinates within each image.
In road scenes, cuboids are used to distinguish vehicles, pavement, pedestrians, etc., by drawing a cube over an object/2D images to get 3D perspectives on height, width, and depth.
Semantic Segmentation allows AI-based perception models to classify and detect objects of interest pixel-by-pixel by segmenting an image into a region delineating meaningful objects.
3D LiDar annotation (Light Detection and Ranging), which is also known as 3D point cloud labeling, allows you to label, visualize, track, and visualize objects using high-precision tools.
Polygon annotation, which makes use of multiple vertices and x and y coordinates, is the right method to make polygonal-shaped objects recognizable to autonomous vehicles and self-driving cars.
Polyline for Lane Detection is a key annotation technique that allows annotators to define directions, divergences, and sidewalks, making roads & streets recognizable to self-driving cars.
As one of the most reputable AI training data platforms, Anolytics facilitates the automobile industry with high-quality training data for AI and machine learning applications aiming to tune self-driving cars. Providing industry-specific data annotations and labeling services backed by 1200 full-time data annotation experts, we are dedicated to supporting automated vehicle engineering with industry-specific AI training data.
The tools we work with are the most advanced available on the market and allow for extremely precise image & video annotation and accurate labeling for use cases like autonomous driving. At Anolytics, we excel at categorizing images and videos frame by frame and annotating & labeling as many characters as possible in unstructured datasets, for example, pedestrians, cars, roads, lampposts, traffic signs, etc., just to provide self-driving vehicles with never-failing self-driving functionality.
Regardless of the size or scope of your machine learning (ML) project, the overall result depends strongly on the quality of the data that is used to train the AI models. A pivotal part of the process is the image and video annotation technique that is harnessed to develop AI training data. Having spanned more than a decade in the AI & machine learning space as a premiere annotation company, Anolytics has mastered various data annotation techniques for use in different AI & ML programs.
As a leading data annotation and labeling expert with half a decade of industry exposure, Anolytics is a perfect choice for your AI training data needs.
Get the best-in-class quality services with highest accuracy level delivering an excellence in image annotation through multiple stages of auditing and reviewing of labeled data.
We are certified with SOC 2 TYPE 1 Company for maintaining the high standards of data security with privacy while working with our clients to ensure their confidentiality.
Working with hundreds of workforce to annotate pictures as per the demand providing a completely scalable solution with turnaround time to meet the different client’ needs.
Image annotation outsourcing to us means our clients get a cost-effective data labeling service helping them to minimize the cost of their project with best efficiency.
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