Annotation Techniques - Labellerr

Annotation Techniques

A collection of 13 posts

Active Learning Model Working Process for Smarter AI

Active Learning: Less Data, Smarter Models

Active learning is a paradigm shift in the traditional supervised learning approach. Unlike passive learning, which relies on a pre-defined, static set of labeled data for training, active learning algorithms actively participate in the data selection process. This blog delves into the core concepts of active learning and its key

Easily Manage Quality Control Of Data Annotation Project With Labellerr

Easily Manage Quality Control Of Data Annotation Project With Labellerr

In Labellerr, we've introduced a handy feature that lets clients or reviewers efficiently assess specific files, i.e., a subset of files. Whether it's evaluating files from a specific date or those linked to particular annotators, the chosen files are easily accessible and seamlessly transitioned to

Streamlining Annotation Feedback Using Labellerr's Remarks Tags

Enhance Collaboration & Communication With Labellerr's Remarks Tags

Table of Contents 1. Introduction 2. Why Is It Needed? 3. How to Make Remarks in Labellerr? 4. Advantages of Using Remarks Tag 5. Conclusion 6. Frequently Asked Questions Introduction We're excited to introduce a powerful new feature to Labellerr: "Remarks Tags." Labellerr is all about

Save Time Reviewing Large Dataset With Quick Grid View Feature

Save Time Reviewing Large Dataset With Quick Grid View Feature

Table of Contents 1. Introduction 2. What Problem Does It Solve? 3. Advantages of Grid View 4. How to Use Grid Feature in Labellerr Platform 5. Conclusion 6. Frequently Asked Questions Introduction We are thrilled to introduce a significant enhancement to Labellerr that will revolutionize your workflow: the grid view

Measure False Positive to Object Detected In One Click With Labellerr

Measure False Positive to Object Detected In One Click With Labellerr

Picture yourself as a data analyst tasked with assessing the accuracy of annotations within a dataset. Analyzing false positives in overall dataset is very crucial for quality assurance. Without Labellerr's latest feature update, your evaluation process is hindered by inaccurate error rate calculations that fail to provide a

Migrate from Labelbox to Labellerr

Migrate from Labelbox to Labellerr

Labelbox is a cloud-based platform for labeling data for various AI applications, including computer vision, natural language processing, and more. It has features like active learning and collaboration tools. Features of LabelBox: Diverse annotation: Labelbox supports a wide range of annotation types, including bounding boxes, polygons, points, text, and audio

Migration from AWS GroundTruth to Labellerr

Migration from AWS GroundTruth to Labellerr

Amazon SageMaker Ground Truth is a service provided by Amazon Web Services (AWS) to help developers and data scientists build highly accurate training datasets for machine learning models. Ground Truth combines human labelers and machine learning algorithms to provide annotations for data. It allows users to efficiently label large datasets

Securely Migrate Data Labeling Tasks From CVAT To Labellerr

Securely Migrate Data Labeling Tasks From CVAT To Labellerr

CVAT stands for Computer Vision Annotation Tool. It is an open-source tool that is designed for annotating images and videos to create datasets for computer vision algorithms. CVAT provides users with a web-based interface that allows easy annotation of objects within images and videos. Features of CVAT: Data Annotation: CVAT

Migrate Data Labeling Project From Label Studio To Labellerr

How To Migrate Data Labeling Project From Label Studio To Labellerr

Label Studio is an open-source data labeling and annotation tool that helps you prepare high-quality training data for machine learning models. Features of Label Studio Flexibility: Label Studio supports various data types like images, text, audio, and video, making it suitable for a wide range of machine learning tasks. Annotation

A complete guide to set up Label Studio

A Complete Guide To Set Up Label Studio

Label Studio is a versatile open-source data annotation tool that empowers machine learning practitioners with a user-friendly interface. Label Studio supports annotation for various data types, including images, text, audio, and video. This flexibility makes it suitable for diverse machine learning tasks. The platform integrates seamlessly with popular machine learning

Geospatial Annotation: Transforming Industries with Labellerr

Geospatial Annotation

Geospatial Image Annotation With Labellerr

Table of Contents 1. What is Geospatial Annotation? 2. Different Geospatial Data Annotation Methods 3. Geospatial Data Annotation Techniques 4. The Challenges of Geospatial Annotation 5. Industries that Stand to Gain from Geospatial Annotation 6. Labellerr: Your Trusted Geospatial Data Annotator Tool 7. Geospatial image formats used in GIS (Geographic

Regulations and Ethical Considerations in Image Annotation

data annotation

Regulations and Ethical Considerations in Image Annotation

When we talk about annotating data, like images or text, it's important to be fair. This means ensuring the labels accurately show what's in the data and not favor specific people or groups. For example, if we're labeling pictures of people, we should include

Ultimate guide to image annotation for AI

Image Annotation

The Ultimate Guide to Image Annotation: Techniques, Tools, and Best Practices

Table of Contents 1. What is Image Annotation? 2. Use Cases in AI and Machine Learning 3. Types of Image Annotation 4. Best Practices for Image Annotation 5. Image Annotation Tools and Software 6. Data Augmentation 7. Transfer Learning 8. Regulations and Ethical Considerations in Image Annotation 9. Future Trends