Drone Imagery based precision agriculture models are eagerly looked forward to, for their potential application to gain insights with seasonal crop yield analysis, soil benefits with input structures, and assistance in various decision matrices to ensure farming sustainability. At AIsmartz, we label data in synergy with agronomists at AgTech companies to annotate sensory and imagery data from both drones and satellites. Our teams help in building highly detail-oriented imagery datasets that train learning models to take into account various landscape factors into consideration which affect crops and plantations on the ground.

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.

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.

Image Classification
(CV)

Our data labellers tag features within imagery data as per client’s model requirements to equip Machine Learning modules that train itself from our labelled dataset of multiclass images and develop a model for future prediction of similar images not encountered during training.

Instance Segmentation
(CV)

CV experts at AIsmartz detect the object and generate a segmentation mask to classify each pixel at object level. Therefore, solving object detection and semantic segmentation together in instance segmentation.

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

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

Let's Connect To Get Started

Planning a machine learning project? AISmartz can help.