With the development of sensor and imagery computing technology, large quantities of geospatial data is generated from a variety of geo/aerial sensors and drones. Annotators at AIsmartz enrich and label to create high-quality training data for machine learning models that run on geospatial imagery to augment the advancement of AI in use cases like agriculture, security, asset management, and more.

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

Point of Interest Marking
(CV)

CV applications with neural networks need to identify important points of interest work best with data inputs that carry coordinates of landmark points and include temporal changes and behavioral trends. We specialize in Point of Interest Marking for Geospatial Technology and landmarking for facial imagery labeling.

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

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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

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Our Client's Speak

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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