NextWealth / Services / Computer Vision / Polygon Annotation Services

Precise and efficient Polygon annotation services by NextWealth for object detection

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High quality Polygon Annotation Service

NextWealth is known for providing highly accurate polygon segmentation for detecting specific shapes in images and training data sets. Using modern tools, we draw pixel-precise polygons by adding and removing points easily allowing us to take your model to the next level.

What is Polygon Annotation

Polygon annotation enables accurate drawing around every corner of a complex structure making it easier for AI models to recognize and respond. This allows capturing of irregular objects allowing labelling and mapping of the elements that are visible in an image. Polygons can not only capture the outline of an object but also eliminate noise that is found within the bounding box which can potentially result in high accuracy. Hence such polygonal techniques are particularly used in making irregularly shaped objects such as road sign boards or different postures of humans in sports recognizable to the computer vision models.

Types of Polygon Annotation

Our polygon annotation services help images to be precisely categorized into specific object categories by classifying individual polygons. Many types of polygon annotations exist for object detection, classification and semantic segmentation.

Detection of irregularly shaped objects

We offer precise labelling of coarse objects and irregularly shaped objects making them recognizable to machine learning models for computer vision.

Semantic Segmentation for irregular shape

We assist the AI models to understand real-world scenarios using polygon segmentation of asymmetrical elements ensuring improved visual perceptions.

Improved Augmentation

We tightly fit annotations in a variety of orientations teaching the object detection model more about different perspectives thereby providing additional information.

Object Localization Services

We annotate both coarse objects in images and unevenly shaped objects such as trees, rooftops, and chimneys captured through drones or satellites for easy localization.

Polygon Annotation Use cases

Labelling and annotation of data using polygons can be applied to a wide variety of Artificial Intelligence and Machine Learning use cases. From automobiles to retail to e-commerce, NextWealth’s data annotation and labelling services are backed by nearly a decade of industry experience.

Agriculture Industry

Polygon image annotation provides accurate detection of various patterns such as bug positions, crop rows and so on enabling computer vision to provide real-time insights from the field resulting in improved crop yield.

Satellites and Drones

Polygon annotation provides high-level precision and contours, enabling satellites and drones to recognize irregular shapes from above, such as rooftops of houses, swimming pools, and trees.

Autonomous Driving

Polygon annotation provides pixel-perfect precision and guidance to autonomous vehicles and helps in improving safety by identifying road boundaries, walkways and other features which might be difficult to see.

Retail

Image annotation services using artificial intelligence and polygonal techniques help create a powerful engine that can provide customers with a personalized shopping experience and make the sale process easier for sellers.

Healthcare

Data annotation techniques like polygon segmentation play a vital role in analyzing and diagnosing various diseases. Machine learning models can be trained on high-precision data sets to improve diagnostics for clinical devices and healthcare.

Robotics

Accurate polygon annotation services with the right labelling provide visual inputs to train robotics and AI models to recognize images and help perform various tasks in many industries.

Case Studies

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FAQs

Can polygon annotation help in increasing AI accuracy?

By utilizing multiple vertices, such as x and y coordinates, the polygon annotation method maps out an object within an image effectively. It is possible to significantly improve the accuracy of computer vision models in dealing with real-world problems by using polygon segmentation, depending on the purpose of the dataset. The NextWealth team leverages the best polygon labelling tools to ensure pinpoint accuracy. Get in touch with us to learn more.

How does polygon annotation recognition work?

Polygon annotations capture more angles and lines clicking at specific points to plot the vertices. Using a descriptive label after annotation makes it easier for machines to understand the object. To train machine learning algorithms, NextWealth offers high-quality datasets for transforming raw data into carefully labelled datasets.

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