Anolytics aims to augment, annotate, and label data accurately, securely, and efficiently by involving humans in the process. Having a rich background in AI, machine learning, and data processing, we are uniquely qualified to provide industry-specific workforce solutions for data annotation & labeling.
We are providing data annotation for machine learning using the advance tools and human powered skills to make each image easily recognizable for machines or computer vision. We can label each data or annotate different types of objects like cars, human, animals or trees etc. using the various modes of annotation as per the client’s needs.
Semantic Segmentation helps to solve the vision problem in outdated computer that involves taking raw data like 2D images as an input and convert them into a mask with areas need to be highlighted. In semantic segmentation masses parts of images together belongs to the same object interested by the users and solve the computer vision problem.
Polygon or Polygonal segmentation will help you to annotate irregular or coarse object that are in asymmetrical shapes. It helps to capture the large images like aerial photography for more precise annotation. Annotate your images with bounding polygons with higher-level of precision to build a sharper and correct vision models for aerial imagery.
Outline the objects using bounding boxes for in depth recognition either its humans, cards or other objects on the streets. We use 2D and 3D bounding box annotation tool depending on your quantity and quality of data. We will help you train the autonomous vehicles recognize such objects with proper tagging and classification to ensure the quality.
Our Image Annotation service is spread over wide-range of industries working on AI-based or machine learning-based business models. From ecommerce to retail and healthcare, we cover most of them with same level of dedication and quality.
As it displays a wide array of topics related to data annotation and labeling, Anolytics' blog posts tend to provide detailed insight into future perspectives of AI and machine learning technology
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