What is the Benefits of Contour Annotations While Creating Image Training Data Sets for AI or ML?

Image data sets annotated with Contour annotations definitely have some benefits. Actually, this method of annotation allows you to place contour labels on the contour plots and represent the numerical value of entire contour line. 
 
Contour Annotations Benefits for Image Data Sets
The best part of this tool is output of this tool is a group layer and contains the input contour features, the annotation layers and the mask polygons in images. 
Contours label automatically as a property of the terrain model element. It heps to create a segmented images for deep learning. This annotation helps to reduce the error, hence would be effective in created data sets for AI development in healthcare.
Higher Accuracy for Computer Vision
The accuracy rate with AI or machine learning model trained with Contours is much more higher than other form of image annotation techniques. Though, annotating with Contours is much more difficult and time taking, which can be only done by the highly experienced annotators to ensure the quality of annotation in each image.
Though, for computer vision contour annotation could be the best data labeling process. However, there are multiple types of image annotation techniques, like bounding box, semantic segmentation, polygon annotation and 3D cuboid annotation and landmark annotation or other popular types of image annotation technique. 
 
To improve the image data sets quality, rather then the technique, the accuracy in image annotation service is more important to ensure to train the ML algorithm with best level of accuracy and ensure the right prediction by the model in real-life use.
Anolytics is providing the image annotation services for machine learning and AI-based model developments. It is creating the image data sets for various sectors including healthcare, retail, automotive, autonomous machines and agriculture etc. It is also known for providing the high-quality training data sets at most affordable pricing. 
Location: United States

Comments

  1. Prayan LearningDecember 11, 2019 at 10:07 PM

    Great blog. An important
    image annotationtechnique which outlines the object in the image with a box, for object classification and localization models.

    ReplyDelete

Post a Comment

Popular posts from this blog

What is Annotation in Machine Learning and Types of Data Annotation in ML?

Image
Annotation means, in machine language simply making the things visible, recognizable or understandable in images, pictures, documents and videos by highlighting or marking or adding footnotes or metadata. And these annotated contents are when used in machine learning becomes the training data for algorithm to learn the different patterns in the data and utilize the same. Data Annotation in Machine Learning         Annotation consists different types of data are annotated as per the machine learning model need and compatibility. And such data consists text, images and videos that contains the useful information about the object of interest that are annotated to make it recognizable to machines through NLP, NLU and computer vision technology used to train the AI-based models. Text Annotation in Machine Learning The language, speech and voice recognition based AI models need data sets that can help them to understand the human language...
Read more

Text Annotations in the News Industry

Image
In the media and communication industry, writers are frequently confronted with huge volumes of textual material. They are having significant difficulty extracting structured knowledge from these papers, and the text is being underutilized, perhaps leaving critical information unknown. Machine learning techniques can assist, but they require a thorough understanding of the information required and manual annotation of the corpus. Before going further, let's understand what annotation, types, and how it is helping machine learning models to perform accurately. What are annotations? Annotation is the process of labeling data which are in the form of image, video, text, or object in order to use Machine Learning to train a model. In simple words, it is the process of transcribing, identifying, and labeling key characteristics in your data. These are the characteristics that you simply want your machine learning system to recognize on its own, with unannotated real-world data. Annotati...
Read more

What is The Difference Between 2D and 3D Image Annotations: Use Cases

Image
Image annotation is the only technique helps machine learning or AI-based perception model to recognize the particular object in an image and learn to detect the such objects when used in real-life. And there are different types of image annotations, like polygon, polylines, landmark, semantic segmentation and bounding box which is one the most common image annotation technique used to make the objects recognizable into 2D and 3D formats. 
Read more