Importance of Data Annotation Tools for Machine Learning

Data annotation is done to create the training data sets for AI and ML.

Machine Learning 

Machine Learning is basically about evolving patterns and manipulating those patterns with different algorithms. In order to evolve, develop and maintain those patterns there is a lot of rich data required through Data Labeling companies because the data needs to represent as many potential outcomes from as many potential scenarios as possible. Quality of Data is very important and also data must have a complete, relevant, and rich context collected from every potential & secure source. 

Data Annotation Tool

A data annotation tool is a cloud-based, on-premise, or containerized software solution that can be used to annotate production-grade training data for machine learning. It’s important to wisely choose the right data annotation tool so as to ensure accurate data for machine learning models. Annotation tools make the annotation process simpler & faster. But sometimes choosing a suitable tool is a time taking and tricky task.  So, the tricky part is to think wisely about your tooling needs now and into the future. 

Tools are made and developed to help annotators work smoothly and make the annotator’s task easier. When the right tool is developed for a particular project it makes the annotation process efficient and effective. 

Then, the raw data is uploaded into the tools so that experience annotators can run through those unstructured data. Categorize & label them accurately so that they deliver data accordingly as per client requirement

Bounding box annotation

Bounding boxes for object detection, classification, and localization in images and videos. Bounding box annotation is basically used to train algorithms to detect the various objects on the streets like lanes, traffic, potholes, signals, and other objects.

Semantic 

Semantic Segmentation is a classic Computer Vision problem which involves taking as input some raw data (2D, 3D images) and labeling the regions of interest highlighted. Semantic segmentation is the process of clustering various parts of images together belonging to the same object class. Leverage our fully-managed human-powered pixel-level image segmentation and annotation to build pixel-perfect semantic segmentation tasks at scale.

LIDAR Annotation and Labeling 

LIDAR stands for Light Detection and Ranging. It is a remote sensing technology emitting light that travels around the object and back to the receiver creating points every time it hits the object building a 3D map of the entire scene. We help annotate or label cars, pedestrians, bicyclists, trees, animals, traffic lights, billboards, garbage bin’s, etc in this map by drawing bounding boxes or cuboids precisely to train the machine learning algorithms to interpret the world.

Learning Spiral provide Data annotation services as our data annotation team is capable of drawing bounding boxes, cuboids, polygon, picture classification/ tagging, text annotation, image masking annotation, data annotation & labeling, 2D & 3D annotation, Semantic segmentation, 3D LIDAR Annotation, autonomous vehicle, tagging of aerial view pictures, drone technology, contour annotation, etc. 

Learning Spiral, Data Labeling company is here to Empower your algorithm with our human labeling services. We help bridge the gap between machines and humans with our reliable labeling and data annotation services.

Let’s Annotate Together

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