Autonomous Vehicles have redefined the concept of mobility and are transforming the entire automotive industry. Whether it is passenger vehicles or commercial trucking, 2D/3D and sensory data annotation plays a pivotal role in preparing wholesome complex training data required to train complex AV algorithms. Our Computer Vision experts label on/off-road driving source information to convert it into high-quality training data. These are quintessential insights required for generating accurate ground truth in your AV models.

Bounding Boxes
(CV)

Computer Vision experts outline artifacts in 2D & 3D for in-depth recognition to identify and classify objects in images and videos for machine learning processes, in use cases such as retail, robotics, drone imagery, and autonomous vehicles.

Polygon Annotation
(CV)

Our data labeling team outlines the exact shape of the target object to annotate its precise edges effectively by drawing pixel-perfect polygons.

Semantic Segmentation
(CV)

We classify and label each pixel of an image for fine-grained understanding. It enables image classification with pixel-wise annotation to localize images with intense precision. AIsmartz team segments multiple types of objects in images belonging to a single class at a pixel level.

LIDAR Annotation
(CV)

3D point cloud annotations are best suited for accurate ground truth realization and rapid labeling of moving objects detected by LiDAR sensors, in both indoor and outdoor environments. Teams at AIsmartz label point clouds in images and videos captured by multi-sensor cameras,

OBJECT TRACKING
(CV)

Data labeling experts at AIsmartz render a deeper understanding of the environment by tracking objects in bounding boxes as they move through a set of video frames. We specialize in object tracking and classification thereby supporting diverse use cases including surveillance, medical

Data Annotation Workflow

Instructions Set

You share your sample data with business rules

Task Analysis

Our annotation experts share their opinion on workforce hours and tools required for the job

Data Labelling with Checks

Once signed up, our teams work in close contact with you for initial 8 weeks to understand edge cases

Production Grade Annotation

QA Managers monitor throughput closely with gold standards, consensus, and sampling

Exported Training Data Feedback

Finished training data run by you for feedback and info on model iterations

SUGGESTED READS

Choosing the right Data Annotation Tool

Since the performance of your ML model is as good as the data that trains it, understanding the tools used for annotating this data becomes especially important. These tools determine the quality of the data and can have implications on the success or failure of your model. … read more

Key Factors to find synergy with Labeling Partner

When we think about AI and Machine Learning, we naturally tend to think of self-driving cars, delivery drones, robot-assisted precision surgeries, and all the technological innovations that have been doing the rounds lately.… read more

Our Client's Speak

Use Cases

Finance and Insurance Tech

We partner with asset management, legal, finance and insurance firms to assist them to embark on their journey of robotic automation of gathering quick insights on lengthy legal, structural and financial data. … read more

Customer Service Automation

With the advent of new generation AI enabled chatbots and virtual assistants, efficient and warm handling of basic queries, assistance replies to product/service oriented feedback is just the tip of the iceberg… read more

Government

Be it e-auction sites, public tenders, taxation, documentary record repositories, or nature, animal, people & demographics information, database management and enrichment is an essential facet of building data authenticity and enhancing user experience... read more

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