DATA ANNOTATION

ground truth annotations

DATA ANNOTATION

ground truth annotations

Data Annotation Solutions

Ground Truth Annotations

Annotatory is a flourishing data annotation company helping companies build data pipelines for precision and Accuracy in Machine learning models.

Annotatory is unarguably the one stop destination for all your data labelling needs.

Our expertise in the domain ,process precision and a keen focus on details helps us deliver outputs at benchmarking speeds and quality.

What we do?

Image Annotation

Image Annotation

Video Annotation

Video Annotation

Text Annotation

Text Annotation

Speech Annotation

Speech Annotation

Different Annotation Techniques

 Annotatory is definitively an annotation services provider that provides ground truth data labeling services at the best prices possible and caters to data of any size and any budget.

These are the common data labeling techniques used for various use cases either individually or in combination to feed highly trained data to machine learning models.

1

Computer Vision

A new concept of showing content in your web page with more interactive way.

Cool Headline

Bounding Box

Bounding boxes are one of the most popular and familiar types of image annotations that are used for machine learning and deep learning purposes. Bounding box annotators are asked to outline the object/class in an image as per the requisites. Being one of the cheapest and least time-consuming annotation methods for AI, bounding boxes are the ideal type of annotation for image object classification.2D-Bounding Boxes: These are the regular bounding boxes that localize and detect the object in images.

Poly Line

The polylines annotations produced here at annotatory help autonomous vehicles in detecting and distinguishing lanes of cars, bicycles, traffic, divergence, etc. These polylines can be best used to estimate lanes and our annotation service here promises quality and precision

Polygon

Bounding boxes are one of the most popular and familiar types of image annotations that are used for machine learning and deep learning purposes. Bounding box annotators are asked to outline the object/class in an image as per the requisites. Being one of the cheapest and least time-consuming annotation methods for AI, bounding boxes are the ideal type of annotation for image object classification.2D-Bounding Boxes: These are the regular bounding boxes that localize and detect the object in images.

Dots or points

The customizable Annotation tool can be used to precisely select and label specific points on 2D and Contour plots.Since  Deep learning algorithms require a large number of properly labelled datasets, 3D point cloud labelling is an important image annotation technique used in training LIDAR. Our team can efficiently deliver large volumes of training datasets to clients, allowing them to easily fuel their computer vision-based models.

Semantic Segmentation

Semantic segmentation annotation is a full pixel segmentation of the image for data labeling and training in computer vision. It can be used for instance segmentation for feature detection- training perception models in non-environmental objects of interest, full pixel semantic segmentation- high utility in autonomous vehicles and safety surveillance cameras where information of every pixel is critical and may influence the accuracy of the perception model, and under panoptic segmentation, the image used is individually segmented into objects of the same class by assigning instance unique IDs to each object.

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1

3d sensor

A new concept of showing content in your web page with more interactive way.

Cool Headline

A new concept of showing content in your web page with more interactive way.

Read More

1

NLP

A new concept of showing content in your web page with more interactive way.

Cool Headline

A new concept of showing content in your web page with more interactive way.

Read More

Industry Specific Annotation

Agriculture Annotation

Annotatory’s advanced AI image annotations helps complex tasks such as early detection of weed growth, pest infestations, plant population/tree count, field health, disease identification be conveniently taken care of with precision focused AI image label training and ariel imaging. We generate precise training data sets for AI and machine learning in agriculture and farming, with quality ensured

Medical AI Annotation

At Annotatory, we aim at providing precision patient care via the use and implementation of AI models,  Cognitive computing, and by building highest-quality medical annotations using computer vision. We offer diagnostic assistance, spatial orientation, medical pathology and more. With Annotatory’s state of the art medical data set training and image labeling

Retail Annotation

We use cutting edge semantic segmentation, video annotation, image, video, 3D-cuboid annotations, Footfall interaction – unique ID Assigning to track and training data sets for labeling. Being mindful of customer sentiments and inclination, our professional annotators will annotate images of shelves, products, brands, and prices for you in the most realistic way possible

Security Annotation

Annotatary helps security  AI solution providers in enhancing the efficiency of their systems by providing ground truth detailed annotation for their deep learning, machine learning and facial recognition systems to differentiate, determine and analyze behavior, environments & abnormalities in the live feed of data. We value the privacy of data and thus annotate all of the data in house.

Autonomous transport Annotation

Annotatory helps you build high-quality ground truth datasets to train for your perception, prediction models & computer vision models, Annotatory’s data annotation solutions help you build data pipelines that will power precision and accuracy for your autonomous applications.

Industrial Automation Annotation​

We enable automation of business processes & manufacturing robots/ machines by annotating the human process of work execution to be able to teach the machine to automate this process, the accuracy is a key factor here as a mistake in one part of the process leads to disruption of the whole output. Manufacturing industry enables automation to use the workforce in skilled areas or to work alongside humans to make processes more efficient and productive, to provide solutions and to eliminate the time spent on important business processes.

Entertainment Annotation

We provide mines the ground truth data they need in order to enable automation and work more efficiently. Mining is an expensive industry and a single mistake can cost millions while also finding the mistake can save millions. Mining companies use our services to gain the maximum amount of insights, establish better control over premises, increase safety and reduce costs. Annotatory focuses on delivering the highest level of data detail for them to make informed decisions and act with the full knowledge of all elements.

Education Annotation​

sentences and numbers to help them develop a rich education learning experience for their users. We help them by eliminating the irrelevant parts of data and by pointing out only the relevant data of the concept. sentences and numbers to help them develop a rich education learning experience for their users. We help them by eliminating the irrelevant parts of data and by pointing out only the relevant data of the concept.

Mining Annotation

We provide mines the ground truth data they need in order to enable automation and work more efficiently. Mining is an expensive industry and a single mistake can cost millions while also finding the mistake can save millions. Mining companies use our services to gain the maximum amount of insights, establish better control over premises, increase safety and reduce costs. Annotatory focuses on delivering the highest level of data detail for them to make informed decisions and act with the full knowledge of all elements.

Bounding Box

Bounding boxes are one of the most popular and familiar types of image annotations that are used for machine learning and deep learning purposes. Bounding box annotators are asked to outline the object/class in an image as per the requisites. Being one of the cheapest and least time-consuming annotation methods for AI, bounding boxes are the ideal type of annotation for image object classification.2D-Bounding Boxes: These are the regular bounding boxes that localize and detect the object in images.

Poly Line

The polylines annotations produced here at annotatory help autonomous vehicles in detecting and distinguishing lanes of cars, bicycles, traffic, divergence, etc. These polylines can be best used to estimate lanes and our annotation service here promises quality and precision

Polygon

Bounding boxes are one of the most popular and familiar types of image annotations that are used for machine learning and deep learning purposes. Bounding box annotators are asked to outline the object/class in an image as per the requisites. Being one of the cheapest and least time-consuming annotation methods for AI, bounding boxes are the ideal type of annotation for image object classification.2D-Bounding Boxes: These are the regular bounding boxes that localize and detect the object in images.

Dots or points

The customizable Annotation tool can be used to precisely select and label specific points on 2D and Contour plots.Since  Deep learning algorithms require a large number of properly labelled datasets, 3D point cloud labelling is an important image annotation technique used in training LIDAR. Our team can efficiently deliver large volumes of training datasets to clients, allowing them to easily fuel their computer vision-based models.

Semantic Segmentation

Semantic segmentation annotation is a full pixel segmentation of the image for data labeling and training in computer vision. It can be used for instance segmentation for feature detection- training perception models in non-environmental objects of interest, full pixel semantic segmentation- high utility in autonomous vehicles and safety surveillance cameras where information of every pixel is critical and may influence the accuracy of the perception model, and under panoptic segmentation, the image used is individually segmented into objects of the same class by assigning instance unique IDs to each object.

Services

Our Locations

Corporate Office

GF -3, 35, Road no 70, Jubliee hills, hyderabad, telangana, 500033.

Branch Office

2025 Gateway Pl #252 San Jose, CA 95110 USA.

Offshore Office

 Floor 2 krishnakanth plaza, Kurnool, Andra Pradesh, 518002.

Services

Corporate Office:

 GF -3, 35, Road no 70, Jubliee hills, hyderabad, telangana, 500033.

Branch Office:

2025 Gateway Pl #252 San Jose, CA 95110 USA.

OffshoreOffice:

 Floor 2 krishnakanth plaza, Kurnool, Andra Pradesh, 518002.