AI Training Datasets for Self-driving Vehicles

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autonomous vehicle annotation

AI Training Datasets for Autonomous Vehicles

The computer vision system of all self-driving vehicles has to be trained and tuned with a large amount of structured, annotated & labeled data. Hence, we develop qualitative, error-free, human-labeled, and cost-effective AI training data for autonomous vehicles.

Data Annotation Tools for Autonomous Vehicles

Bounding Box for Object Detection

Bounding Box for Object Detection

Bounding boxes are drawn over images by data annotators as points of reference for object detection. This is used for outlining objects of interest with well-defined coordinates within each image.

3D Cuboid for Precise Dimension

Cuboids are used for distinguishing vehicles, pavement, pedestrians, etc by drawing a cube over an object/2D images for obtaining 3D perspectives on height, width, and depth.

 3D Cuboid for Precise Dimension
Semantic Segmentation for Image Classification

Semantic Segmentation for Image Classification

Semantic segmentation allows AI-based perception models to classify and detect objects of interest minutely by segmenting and delineating an image into a region.

3D Point Cloud for LiDARs

Also known as 3D LiDAR annotation, this technique is used for labeling, visualization, and tracking with the use of high precision tools.

3D Point Cloud for LiDARs
Polygon for Irregular Shapes

Polygon for Irregular Shapes

This technique utilizes multiple vertices and x and y coordinates for making polygonal-shaped objects recognizable to autonomous vehicles.

Polyline for Lane Detection

This technique permits annotators to define directions, divergences, and sidewalks for making roads and streets recognizable to autonomous vehicles.

Polyline for Lane Detection

Top Two Reasons to Choose Anolytics for Automobile Automation

Reason #1

We facilitate the automobile industry with high quality training data for AI and machine learning applications with the aim of tuning self-driving cars. We provide industry specific data annotation and labeling services backed by 1200 full-time data annotation experts.

Reason #2

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., to provide self-driving vehicles with never-failing self-driving functionality.

Interested in Working with Us?

In today's tech-driven world, a career in Artificial Intelligence (AI) can be highly rewarding. Join our team of Annotation Specialist, and be a part of the company that creates high-quality training datasets.

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