“With the streamlined design of Labelbox, we are able to cut costs on labeling by as much as 50% while maintaining the highest quality in our training data, and get to training our models faster. With human-in-the-loop model-assisted labeling, we expect another huge reduction in time and costs to the labeling process. After a preliminary model is trained, we can run a loop to generate labels from our model’s inference, and feed those back into Labelbox, effectively cutting the labeling load of our labelers to that of reviewing for false positives. That allows us to increase our capabilities and model accuracies exponentially with respect to time for the amount of components and defects we can detect and classify.”
Data Analyst / AI
Only a few years ago, sensor and robotics manufacturers typically just sold hardware. Today, these devices often come with edge AI applications that delivers alerts — whether someone is at your door or someone is not wearing a hard hat in a construction site. This paradigm shift means that sensor manufacturers need to transform into builders of powerful, reliable AI.
Many enterprises that require inspection and quality control for assembly lines, utility structures, or other processes are cutting costs by implementing computer vision AI solutions that monitor products and systems and generate alerts. Labelbox empowers AI teams that utilize sensors and robotics to build these solutions with powerful and intuitive labeling tools for many types of images and videos.Learn more
For situations where false alarms are costly and time consuming, enterprises can use a human in the loop system, where a person can review AI decisions before it generates an alert. Labelbox provides a feedback system that dlivers an intuitive review and approval UI for those monitoring AI decisions and moves information seamlessly via cloud networks to end users.
Develop geospatial AI solutions faster than your competitors. Labelbox provides native support for geospatial data across all products, so you can visualize and search raw data, label data, and train powerful models quickly.Learn more
Computer vision AI trained on images can realize remarkable results, from identifying defective products to recognizing faces. Models trained on video data, however, have the ability to do more: they can track objects over time. Labelbox empowers AI teams that utilize sensors and robotics to visualize and sort video data, label it efficiently and accurately, and train the next generation of computer vision AI solutions.Learn more
Whether your AI team requires operations setup, training, data labelers experienced with your industry and use case, or just some extra support, Labelbox is ready to give your team the boost it needs.
How VirtuSense built an AI data engine that dramatically increased model performance
The VirtuSense team struggled to distribute unstructured data to the labeling team and track progress in an efficient manner. With their open source tools, the lack of immediate support when issues cropped up became yet another blocker for the team.
The VirtuSense team designed a data engine with labelbox to automate every aspect of the model iteration loop, so that the only human involvement required is that of their labelers as they annotate data.
Since Labelbox, VirtuSense is now been able to increase the amount of labels created by 5X. Their team has now produced over one million labeled assets. Their false alarm rates have fallen from roughly 28% to 6%, and the daily average number of alerts have dropped from seven to five. Their average accuracy has increased by over 20%.