How Annotation Tools Can Streamline Management

Feb 15, 2022

The advances currently occurring in computer vision based AI are undergirded by the production of huge quantities of annotated image and video training data. Managing a large data annotation task for an AI project can be a daunting task.

An outsourced, disparate workforce can make communication and collaboration difficult and result in labeling tasks missing deadlines or producing poor quality datasets. Lapses in quality at the data annotation stage will undoubtedly produce models with sub-optimal performance.

Commercially available annotation tools, like Keylabs, are helping to streamline the management of annotation for computer vision by giving developers more control over labeling work through user friendly interfaces and in-depth analytics. This blog will address more of the management challenges facing AI innovators and reveal how annotation tools are helping overcome them.

The Challenges of Managing Annotation

Management is perhaps the key challenge of data annotation. Individuals in leadership positions and senior members of staff may find themselves devoting a significant amount of time to the administration and management of large data annotation teams.

The burden of troubleshooting and safeguarding quality in training datasets also falls upon these key individuals. Data annotation can distract innovators and experts from their core mission.

Quality control is an added complexity of the annotation process. Managers may have to communicate the specific demands of a project across different time zones and cultural contexts. This can lead to issues with quality down the line.

Remote workers may not be familiar with different annotation tools. This can mean that progress is slower as more training is required. Troubleshooting can be extremely time consuming as issues have to be identified and rectified across a disparate workforce.

Annotation tool | Keylabs

Annotation Tools Empower Managers

The management troubles inherent to data annotation are significant. However, there is substantial evidence that they can be mitigated by well designed commercial annotation tools. Keylabs is an annotation tool that deploys a variety of bespoke features to overcome the challenges of annotation management:

  • Visibility: A well designed and user-friendly interface allows managers far greater insight into the status of an annotation project. The project road map can be easily visualised with the correct UI allowing for greater control and flexibility for managers at a glance.
  • Planning and Task Assignment: Planning workflows and assigning tasks can be accomplished with a few clicks of a mouse with a responsive video or image annotation tool. This functionality allows managers to allocate labeling tasks promptly and accurately.
  • Workforce Analytics: Being able to take a granular look at the work done by individual annotators is a significant advantage for managers. Keylabs provides managers with detailed analytics of every action taken, allowing them to advise annotators and improve productivity.
  • Quality Control: Quality control is the final safeguard for usable image and video datasets. Built inequality control features improves workflows and provides managers with actionable data. Keylabs reviews annotations, grades accuracy, flags errors, and assigns annotations to your teams based on performance.
  • Communication and Collaboration: By improving visibility of data in the annotation process, commercial annotation tools are essential for improving communication and collaboration between managers and annotators. By tracking errors, and improving workflow and efficiency commercial annotation tools are a vital component of scalable image and video annotation.

Management Facilitated by Keylabs

Keylabs is an annotation tool designed and built by annotation specialists. This state-of-the-art platform combines a user-friendly interface with high performance annotation features and management options.

Contact a team member to book your personalized demo today.

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